/*====================================================================* - Copyright (C) 2001 Leptonica. All rights reserved. - - Redistribution and use in source and binary forms, with or without - modification, are permitted provided that the following conditions - are met: - 1. Redistributions of source code must retain the above copyright - notice, this list of conditions and the following disclaimer. - 2. Redistributions in binary form must reproduce the above - copyright notice, this list of conditions and the following - disclaimer in the documentation and/or other materials - provided with the distribution. - - THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS - ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT - LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR - A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL ANY - CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, - EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, - PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR - PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY - OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING - NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS - SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. *====================================================================*/ /*! * \file colorcontent.c *
 *
 *      Build an image of the color content, on a per-pixel basis,
 *      as a measure of the amount of divergence of each color
 *      component (R,G,B) from gray.
 *         l_int32    pixColorContent()
 *
 *      Find the 'amount' of color in an image, on a per-pixel basis,
 *      as a measure of the difference of the pixel color from gray.
 *         PIX       *pixColorMagnitude()
 *
 *      Find the fraction of pixels with "color" that are not close to black
 *         l_int32    pixColorFraction()
 *
 *      Do a linear TRC to map colors so that the three input reference
 *      values go to white.  These three numbers are typically the median
 *      or average background values.
 *         PIX       *pixColorShiftWhitePoint()
 *
 *      Generate a mask over pixels that have sufficient color and
 *      are not too close to gray pixels.
 *         PIX       *pixMaskOverColorPixels()
 *
 *      Generate a mask over dark pixels with little color
 *         PIX       *pixMaskOverGrayPixels()
 *
 *      Generate mask over pixels within a prescribed cube in RGB space
 *         PIX       *pixMaskOverColorRange()
 *
 *      Determine if there are significant color regions that are
 *      not background in a page image
 *         l_int32    pixFindColorRegions()
 *
 *      Find the number of perceptually significant gray intensities
 *      in a grayscale image.
 *         l_int32    pixNumSignificantGrayColors()
 *
 *      Identify images where color quantization will cause posterization
 *      due to the existence of many colors in low-gradient regions.
 *         l_int32    pixColorsForQuantization()
 *
 *      Find the number of unique colors in an image
 *         l_int32    pixNumColors()
 *
 *      Lossless conversion of RGB image to colormapped
 *         PIX       *pixConvertRGBToCmapLossless()
 *
 *      Find the most "populated" colors in the image (and quantize)
 *         l_int32    pixGetMostPopulatedColors()
 *         PIX       *pixSimpleColorQuantize()
 *
 *      Construct a color histogram based on rgb indices
 *         NUMA      *pixGetRGBHistogram()
 *         l_int32    makeRGBIndexTables()
 *         l_int32    getRGBFromIndex()
 *
 *      Identify images that have highlight (red) color
 *         l_int32    pixHasHighlightRed()
 *
 *  Color is tricky.  If we consider gray (r = g = b) to have no color
 *  content, how should we define the color content in each component
 *  of an arbitrary pixel, as well as the overall color magnitude?
 *
 *  I can think of three ways to define the color content in each component:
 *
 *  (1) Linear.  For each component, take the difference from the average
 *      of all three.
 *  (2) Linear.  For each component, take the difference from the average
 *      of the other two.
 *  (3) Nonlinear.  For each component, take the minimum of the differences
 *      from the other two.
 *
 *  How might one choose from among these?  Consider two different situations:
 *  (a) r = g = 0, b = 255            {255}   /255/   <255>
 *  (b) r = 0, g = 127, b = 255       {191}   /128/   <255>
 *  How much g is in each of these?  The three methods above give:
 *  (a)  1: 85   2: 127   3: 0        [85]
 *  (b)  1: 0    2: 0     3: 127      [0]
 *  How much b is in each of these?
 *  (a)  1: 170  2: 255   3: 255      [255]
 *  (b)  1: 127  2: 191   3: 127      [191]
 *  The number I'd "like" to give is in [].  (Please don't ask why, it's
 *  just a feeling.
 *
 *  So my preferences seem to be somewhere between (1) and (2).
 *  (3) is just too "decisive!"  Let's pick (2).
 *
 *  We also allow compensation for white imbalance.  For each
 *  component, we do a linear TRC (gamma = 1.0), where the black
 *  point remains at 0 and the white point is given by the input
 *  parameter.  This is equivalent to doing a global remapping,
 *  as with pixGlobalNormRGB(), followed by color content (or magnitude)
 *  computation, but without the overhead of first creating the
 *  white point normalized image.
 *
 *  Another useful property is the overall color magnitude in the pixel.
 *  For this there are again several choices, such as:
 *      (a) rms deviation from the mean
 *      (b) the average L1 deviation from the mean
 *      (c) the maximum (over components) of one of the color
 *          content measures given above.
 *
 *  For now, we will consider three of the methods in (c):
 *    L_INTERMED_DIFF
 *        Define the color magnitude as the intermediate value of the
 *        three differences between the three components.
 *        For (a) and (b) above, this value is in /../.
 *     L_AVE_MAX_DIFF_2
 *        Define the color magnitude as the maximum over components
 *        of the difference between the component value and the
 *        average of the other two.  It is easy to show that
 *        this is equivalent to selecting the two component values
 *        that are closest to each other, averaging them, and
 *        using the distance from that average to the third component.
 *        For (a) and (b) above, this value is in {..}.
 *    L_MAX_DIFF
 *        Define the color magnitude as the maximum value of the
 *        three differences between the three components.
 *        For (a) and (b) above, this value is in <..>.
 * 
*/ #ifdef HAVE_CONFIG_H #include #endif /* HAVE_CONFIG_H */ #include "allheaders.h" /* ----------------------------------------------------------------------- * * Build an image of the color content, on a per-pixel basis, * * as a measure of the amount of divergence of each color * * component (R,G,B) from gray. * * ----------------------------------------------------------------------- */ /*! * \brief pixColorContent() * * \param[in] pixs 32 bpp rgb or 8 bpp colormapped * \param[in] rref reference value for red component * \param[in] gref reference value for green component * \param[in] bref reference value for blue component * \param[in] mingray min gray value for which color is measured * \param[out] ppixr [optional] 8 bpp red 'content' * \param[out] ppixg [optional] 8 bpp green 'content' * \param[out] ppixb [optional] 8 bpp blue 'content' * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) This returns the color content in each component, which is
 *          a measure of the deviation from gray, and is defined
 *          as the difference between the component and the average of
 *          the other two components.  See the discussion at the
 *          top of this file.
 *      (2) The three numbers (rref, gref and bref) can be thought
 *          of in two ways:
 *            (a) as the values in the image corresponding to white,
 *                to compensate for an unbalanced color white point.
 *            (b) the median or mean values of the background color of
 *                a scan.
 *          The gamma TRC transformation is used to modify all colors so that
 *          these reference values become white.
 *          These three numbers must either be all 0 or all non-zero.
 *          To skip the TRC transform, set them all to 0.
 *      (3) If the maximum component after white point correction,
 *          max(r,g,b), is less than mingray, all color components
 *          for that pixel are set to zero.
 *          Use mingray = 0 to turn off this filtering of dark pixels.
 *      (4) Therefore, use 0 for all four input parameters if the color
 *          magnitude is to be calculated without either white balance
 *          correction or dark filtering.
 * 
*/ l_ok pixColorContent(PIX *pixs, l_int32 rref, l_int32 gref, l_int32 bref, l_int32 mingray, PIX **ppixr, PIX **ppixg, PIX **ppixb) { l_int32 w, h, i, j, wpl1, wplr, wplg, wplb; l_int32 rval, gval, bval, rgdiff, rbdiff, gbdiff, maxval, colorval; l_uint32 pixel; l_uint32 *data1, *datar, *datag, *datab, *line1, *liner, *lineg, *lineb; PIX *pix1, *pixr, *pixg, *pixb; PROCNAME("pixColorContent"); if (!ppixr && !ppixg && !ppixb) return ERROR_INT("no return val requested", procName, 1); if (ppixr) *ppixr = NULL; if (ppixg) *ppixg = NULL; if (ppixb) *ppixb = NULL; if (!pixs) return ERROR_INT("pixs not defined", procName, 1); if (mingray < 0) mingray = 0; if (mingray > 255) return ERROR_INT("mingray > 255", procName, 1); /* Do the optional linear color map; this checks the ref vals */ if ((pix1 = pixColorShiftWhitePoint(pixs, rref, gref, bref)) == NULL) return ERROR_INT("pix1 not returned", procName, 1); pixr = pixg = pixb = NULL; pixGetDimensions(pix1, &w, &h, NULL); if (ppixr) { pixr = pixCreate(w, h, 8); datar = pixGetData(pixr); wplr = pixGetWpl(pixr); *ppixr = pixr; } if (ppixg) { pixg = pixCreate(w, h, 8); datag = pixGetData(pixg); wplg = pixGetWpl(pixg); *ppixg = pixg; } if (ppixb) { pixb = pixCreate(w, h, 8); datab = pixGetData(pixb); wplb = pixGetWpl(pixb); *ppixb = pixb; } data1 = pixGetData(pix1); wpl1 = pixGetWpl(pix1); for (i = 0; i < h; i++) { line1 = data1 + i * wpl1; if (pixr) liner = datar + i * wplr; if (pixg) lineg = datag + i * wplg; if (pixb) lineb = datab + i * wplb; for (j = 0; j < w; j++) { pixel = line1[j]; extractRGBValues(pixel, &rval, &gval, &bval); if (mingray > 0) { /* dark pixels have no color value */ maxval = L_MAX(rval, gval); maxval = L_MAX(maxval, bval); if (maxval < mingray) continue; /* colorval = 0 for each component */ } rgdiff = L_ABS(rval - gval); rbdiff = L_ABS(rval - bval); gbdiff = L_ABS(gval - bval); if (pixr) { colorval = (rgdiff + rbdiff) / 2; SET_DATA_BYTE(liner, j, colorval); } if (pixg) { colorval = (rgdiff + gbdiff) / 2; SET_DATA_BYTE(lineg, j, colorval); } if (pixb) { colorval = (rbdiff + gbdiff) / 2; SET_DATA_BYTE(lineb, j, colorval); } } } pixDestroy(&pix1); return 0; } /* ----------------------------------------------------------------------- * * Find the 'amount' of color in an image, on a per-pixel basis, * * as a measure of the difference of the pixel color from gray. * * ----------------------------------------------------------------------- */ /*! * \brief pixColorMagnitude() * * \param[in] pixs 32 bpp rgb or 8 bpp colormapped * \param[in] rref reference value for red component * \param[in] gref reference value for green component * \param[in] bref reference value for blue component * \param[in] type chooses the method for calculating the color magnitude: * L_INTERMED_DIFF, L_AVE_MAX_DIFF_2, L_MAX_DIFF * \return pixd 8 bpp, amount of color in each source pixel, * or NULL on error * *
 * Notes:
 *      (1) For an RGB image, a gray pixel is one where all three components
 *          are equal.  We define the amount of color in an RGB pixel as
 *          a function depending on the absolute value of the differences
 *          between the three color components.  Consider the two largest
 *          of these differences.  The pixel component in common to these
 *          two differences is the color farthest from the other two.
 *          The color magnitude in an RGB pixel can be taken as one
 *          of these three definitions:
 *            (a) The minimum value of these two differences.  This is
 *                the intermediate value of the three distances between
 *                component values.
 *            (b) The average of these two differences.  This is the
 *                average distance from the two components that are
 *                nearest to each other to the third component.
 *            (c) The maximum difference between component values.
 *      (2) As an example, suppose that R and G are the closest in
 *          magnitude.  Then the color is determined as either:
 *            (a) The minimum distance of B from these two:
 *                   min(|B - R|, |B - G|).
 *            (b) The average distance of B from these two:
 *                   (|B - R| + |B - G|) / 2
 *            (c) The maximum distance of B from these two:
 *                   max(|B - R|, |B - G|)
 *      (3) This example can be visualized graphically.  Put the R,G and B
 *          component values on a line; e.g.,
 *                G...R...........B
 *            (a) B - R
 *            (b) B - (R + G) / 2
 *            (c) B - G
 *      (4) The three methods for choosing the color magnitude from
 *          the components are selected with these flags:
 *            (a) L_INTERMED_DIFF
 *            (b) L_AVE_MAX_DIFF_2
 *            (c) L_MAX_DIFF
 *      (5) The three numbers (rref, gref and bref) can be thought
 *          of in two ways:
 *            (a) as the values in the image corresponding to white,
 *                to compensate for an unbalanced color white point.
 *            (b) the median or mean values of the background color of
 *                a scan.
 *          The gamma TRC transformation is used to modify all colors so that
 *          these reference values become white.
 *          These three numbers must either be all 0 or all non-zero.
 *          To skip the TRC transform, set them all to 0.
 * 
*/ PIX * pixColorMagnitude(PIX *pixs, l_int32 rref, l_int32 gref, l_int32 bref, l_int32 type) { l_int32 w, h, i, j, wpl1, wpld; l_int32 rval, gval, bval, rdist, gdist, bdist, colorval; l_int32 rgdist, rbdist, gbdist, mindist, maxdist, minval, maxval; l_uint32 pixel; l_uint32 *data1, *datad, *line1, *lined; PIX *pix1, *pixd; PROCNAME("pixColorMagnitude"); if (!pixs) return (PIX *)ERROR_PTR("pixs not defined", procName, NULL); if (type != L_INTERMED_DIFF && type != L_AVE_MAX_DIFF_2 && type != L_MAX_DIFF) return (PIX *)ERROR_PTR("invalid type", procName, NULL); /* Do the optional linear color map; this checks the ref vals */ if ((pix1 = pixColorShiftWhitePoint(pixs, rref, gref, bref)) == NULL) return (PIX *)ERROR_PTR("pix1 not returned", procName, NULL); pixGetDimensions(pix1, &w, &h, NULL); pixd = pixCreate(w, h, 8); datad = pixGetData(pixd); wpld = pixGetWpl(pixd); data1 = pixGetData(pix1); wpl1 = pixGetWpl(pix1); for (i = 0; i < h; i++) { line1 = data1 + i * wpl1; lined = datad + i * wpld; for (j = 0; j < w; j++) { pixel = line1[j]; extractRGBValues(pixel, &rval, &gval, &bval); if (type == L_INTERMED_DIFF) { rgdist = L_ABS(rval - gval); rbdist = L_ABS(rval - bval); gbdist = L_ABS(gval - bval); maxdist = L_MAX(rgdist, rbdist); if (gbdist >= maxdist) { colorval = maxdist; } else { /* gbdist is smallest or intermediate */ mindist = L_MIN(rgdist, rbdist); colorval = L_MAX(mindist, gbdist); } } else if (type == L_AVE_MAX_DIFF_2) { rdist = ((gval + bval ) / 2 - rval); rdist = L_ABS(rdist); gdist = ((rval + bval ) / 2 - gval); gdist = L_ABS(gdist); bdist = ((rval + gval ) / 2 - bval); bdist = L_ABS(bdist); colorval = L_MAX(rdist, gdist); colorval = L_MAX(colorval, bdist); } else { /* type == L_MAX_DIFF */ minval = L_MIN(rval, gval); minval = L_MIN(minval, bval); maxval = L_MAX(rval, gval); maxval = L_MAX(maxval, bval); colorval = maxval - minval; } SET_DATA_BYTE(lined, j, colorval); } } pixDestroy(&pix1); return pixd; } /* ----------------------------------------------------------------------- * * Find the fraction of pixels with "color" that are not close to black * * ----------------------------------------------------------------------- */ /*! * \brief pixColorFraction() * * \param[in] pixs 32 bpp rgb * \param[in] darkthresh threshold near black; if the largest (lightest) * component is below this, the pixel is not * considered in the statistics; typ. 20 * \param[in] lightthresh threshold near white; if the smallest (darkest) * component is above this, the pixel is not * considered in the statistics; typ. 244 * \param[in] diffthresh thresh for the maximum difference between * component values; below this the pixel is not * considered to have sufficient color * \param[in] factor subsampling factor * \param[out] ppixfract fraction of pixels in intermediate * brightness range that were considered * for color content * \param[out] pcolorfract fraction of pixels that meet the * criterion for sufficient color; 0.0 on error * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) This function is asking the question: to what extent does the
 *          image appear to have color?   The amount of color a pixel
 *          appears to have depends on both the deviation of the
 *          individual components from their average and on the average
 *          intensity itself.  For example, the color will be much more
 *          obvious with a small deviation from white than the same
 *          deviation from black.
 *      (2) Any pixel that meets these three tests is considered a
 *          colorful pixel:
 *            (a) the lightest component must equal or exceed %darkthresh
 *            (b) the darkest component must not exceed %lightthresh
 *            (c) the max difference between components must equal or
 *                exceed %diffthresh.
 *      (3) The dark pixels are removed from consideration because
 *          they don't appear to have color.
 *      (4) The very lightest pixels are removed because if an image
 *          has a lot of "white", the color fraction will be artificially
 *          low, even if all the other pixels are colorful.
 *      (5) If pixfract is very small, there are few pixels that are neither
 *          black nor white.  If colorfract is very small, the pixels
 *          that are neither black nor white have very little color
 *          content.  The product 'pixfract * colorfract' gives the
 *          fraction of pixels with significant color content.
 *      (6) One use of this function is as a preprocessing step for median
 *          cut quantization (colorquant2.c), which does a very poor job
 *          splitting the color space into rectangular volume elements when
 *          all the pixels are near the diagonal of the color cube.  For
 *          octree quantization of an image with only gray values, the
 *          2^(level) octcubes on the diagonal are the only ones
 *          that can be occupied.
 * 
*/ l_ok pixColorFraction(PIX *pixs, l_int32 darkthresh, l_int32 lightthresh, l_int32 diffthresh, l_int32 factor, l_float32 *ppixfract, l_float32 *pcolorfract) { l_int32 i, j, w, h, wpl, rval, gval, bval, minval, maxval; l_int32 total, npix, ncolor; l_uint32 pixel; l_uint32 *data, *line; PROCNAME("pixColorFraction"); if (ppixfract) *ppixfract = 0.0; if (pcolorfract) *pcolorfract = 0.0; if (!ppixfract || !pcolorfract) return ERROR_INT("&pixfract and &colorfract not defined", procName, 1); if (!pixs || pixGetDepth(pixs) != 32) return ERROR_INT("pixs not defined or not 32 bpp", procName, 1); pixGetDimensions(pixs, &w, &h, NULL); data = pixGetData(pixs); wpl = pixGetWpl(pixs); npix = ncolor = total = 0; for (i = 0; i < h; i += factor) { line = data + i * wpl; for (j = 0; j < w; j += factor) { total++; pixel = line[j]; extractRGBValues(pixel, &rval, &gval, &bval); minval = L_MIN(rval, gval); minval = L_MIN(minval, bval); if (minval > lightthresh) /* near white */ continue; maxval = L_MAX(rval, gval); maxval = L_MAX(maxval, bval); if (maxval < darkthresh) /* near black */ continue; npix++; if (maxval - minval >= diffthresh) ncolor++; } } if (npix == 0) { L_WARNING("No pixels found for consideration\n", procName); return 0; } *ppixfract = (l_float32)npix / (l_float32)total; *pcolorfract = (l_float32)ncolor / (l_float32)npix; return 0; } /* ----------------------------------------------------------------------- * * Do a linear TRC to map colors so that the three input reference * * values go to white. These three numbers are typically the median * * or average background values. * * ----------------------------------------------------------------------- */ /*! * \brief pixColorShiftWhitePoint() * * \param[in] pixs 32 bpp rgb or 8 bpp colormapped * \param[in] rref reference value for red component * \param[in] gref reference value for green component * \param[in] bref reference value for blue component * \return pix2 32 bpp if OK, NULL on error * *
 * Notes:
 *      (1) This returns a pix where the colors are linearly mapped to
 *          so that the components go to 255 at the input reference values.
 *      (2) These three numbers (rref, gref and bref) can be thought
 *          of in two ways:
 *            (a) as the values in the image corresponding to white,
 *                to compensate for an unbalanced color white point.
 *            (b) the median or mean values of the background color of
 *                an image.
 *          A linear (gamma = 1) TRC transformation is used.
 *      (3) Any existing colormap is removed and a 32 bpp rgb pix is returned.
 *      (4) No transformation is applied if any of the three numbers are <= 0.
 *          If any are < 0, or if some but not all are 0, a warning is given.
 * 
*/ PIX * pixColorShiftWhitePoint(PIX *pixs, l_int32 rref, l_int32 gref, l_int32 bref) { l_int32 w, h, i, j, wpl1, wpl2, rval, gval, bval; l_int32 *rtab, *gtab, *btab; l_uint32 pixel; l_uint32 *data1, *data2, *line1, *line2; NUMA *nar, *nag, *nab; PIX *pix1, *pix2; PIXCMAP *cmap; PROCNAME("pixColorShiftWhitePoint"); if (!pixs) return (PIX *)ERROR_PTR("pixs not defined", procName, NULL); cmap = pixGetColormap(pixs); if (!cmap && pixGetDepth(pixs) != 32) return (PIX *)ERROR_PTR("pixs neither cmapped nor 32 bpp", procName, NULL); if (cmap) pix1 = pixRemoveColormap(pixs, REMOVE_CMAP_TO_FULL_COLOR); else pix1 = pixClone(pixs); if (!rref && !gref && !bref) /* all 0; no transform requested */ return pix1; /* Some ref values are < 0, or some (but not all) are 0 */ if ((rref < 0 || gref < 0 || bref < 0) || (rref * gref * bref == 0)) { L_WARNING("invalid set of ref values\n", procName); return pix1; } /* All white point ref values > 0; do transformation */ pixGetDimensions(pix1, &w, &h, NULL); pix2 = pixCreate(w, h, 32); data1 = pixGetData(pix1); wpl1 = pixGetWpl(pix1); data2 = pixGetData(pix2); wpl2 = pixGetWpl(pix2); nar = numaGammaTRC(1.0, 0, rref); rtab = numaGetIArray(nar); nag = numaGammaTRC(1.0, 0, gref); gtab = numaGetIArray(nag); nab = numaGammaTRC(1.0, 0, bref); btab = numaGetIArray(nab); for (i = 0; i < h; i++) { line1 = data1 + i * wpl1; line2 = data2 + i * wpl2; for (j = 0; j < w; j++) { pixel = line1[j]; extractRGBValues(pixel, &rval, &gval, &bval); rval = rtab[rval]; gval = gtab[gval]; bval = btab[bval]; composeRGBPixel(rval, gval, bval, line2 + j); } } numaDestroy(&nar); numaDestroy(&nag); numaDestroy(&nab); LEPT_FREE(rtab); LEPT_FREE(gtab); LEPT_FREE(btab); pixDestroy(&pix1); return pix2; } /* ----------------------------------------------------------------------- * * Generate a mask over pixels that have sufficient color and * * are not too close to gray pixels. * * ----------------------------------------------------------------------- */ /*! * \brief pixMaskOverColorPixels() * * \param[in] pixs 32 bpp rgb or 8 bpp colormapped * \param[in] threshdiff threshold for minimum of the max difference * between components * \param[in] mindist min allowed distance from nearest non-color pixel * \return pixd 1 bpp, mask over color pixels, or NULL on error * *
 * Notes:
 *      (1) The generated mask identifies each pixel as either color or
 *          non-color.  For a pixel to be color, it must satisfy two
 *          constraints:
 *            (a) The max difference between the r,g and b components must
 *                equal or exceed a threshold %threshdiff.
 *            (b) It must be at least %mindist (in an 8-connected way)
 *                from the nearest non-color pixel.
 *      (2) The distance constraint (b) is only applied if %mindist > 1.
 *          For example, if %mindist == 2, the color pixels identified
 *          by (a) are eroded by a 3x3 Sel.  In general, the Sel size
 *          for erosion is 2 * (%mindist - 1) + 1.
 *          Why have this constraint?  In scanned images that are
 *          essentially gray, color artifacts are typically introduced
 *          in transition regions near sharp edges that go from dark
 *          to light, so this allows these transition regions to be removed.
 * 
*/ PIX * pixMaskOverColorPixels(PIX *pixs, l_int32 threshdiff, l_int32 mindist) { l_int32 w, h, d, i, j, wpls, wpld, size; l_int32 rval, gval, bval, minval, maxval; l_uint32 *datas, *datad, *lines, *lined; PIX *pixc, *pixd; PIXCMAP *cmap; PROCNAME("pixMaskOverColorPixels"); if (!pixs) return (PIX *)ERROR_PTR("pixs not defined", procName, NULL); pixGetDimensions(pixs, &w, &h, &d); cmap = pixGetColormap(pixs); if (!cmap && d != 32) return (PIX *)ERROR_PTR("pixs not cmapped or 32 bpp", procName, NULL); if (cmap) pixc = pixRemoveColormap(pixs, REMOVE_CMAP_TO_FULL_COLOR); else pixc = pixClone(pixs); if (!pixc || pixGetDepth(pixc) != 32) { pixDestroy(&pixc); return (PIX *)ERROR_PTR("rgb pix not made", procName, NULL); } pixd = pixCreate(w, h, 1); datad = pixGetData(pixd); wpld = pixGetWpl(pixd); datas = pixGetData(pixc); wpls = pixGetWpl(pixc); for (i = 0; i < h; i++) { lines = datas + i * wpls; lined = datad + i * wpld; for (j = 0; j < w; j++) { extractRGBValues(lines[j], &rval, &gval, &bval); minval = L_MIN(rval, gval); minval = L_MIN(minval, bval); maxval = L_MAX(rval, gval); maxval = L_MAX(maxval, bval); if (maxval - minval >= threshdiff) SET_DATA_BIT(lined, j); } } if (mindist > 1) { size = 2 * (mindist - 1) + 1; pixErodeBrick(pixd, pixd, size, size); } pixDestroy(&pixc); return pixd; } /* ----------------------------------------------------------------------- * * Generate a mask over dark pixels with little color * * ----------------------------------------------------------------------- */ /*! * \brief pixMaskOverGrayPixels() * * \param[in] pixs 32 bpp rgb * \param[in] maxlimit only consider pixels with max component <= %maxlimit * \param[in] satlimit only consider pixels with saturation <= %satlimit * \return pixd (1 bpp), or NULL on error * *
 * Notes:
 *      (1) This generates a mask over rgb pixels that are gray (i.e.,
 *          have low saturation) and are not too bright.  For example, if
 *          we know that the gray pixels in %pixs have saturation
 *          (max - min) less than 10, and brightness (max) less than 200,
 *             pixMaskOverGrayPixels(pixs, 220, 10)
 *          will generate a mask over the gray pixels.  Other pixels that
 *          are not too dark and have a relatively large saturation will
 *          be little affected.
 *      (2) The algorithm is related to pixDarkenGray().
 * 
*/ PIX * pixMaskOverGrayPixels(PIX *pixs, l_int32 maxlimit, l_int32 satlimit) { l_int32 w, h, i, j, wpls, wpld; l_int32 rval, gval, bval, minrg, min, maxrg, max, sat; l_uint32 *datas, *datad, *lines, *lined; PIX *pixd; PROCNAME("pixMaskOverGrayPixels"); if (!pixs || pixGetDepth(pixs) != 32) return (PIX *)ERROR_PTR("pixs undefined or not 32 bpp", procName, NULL); if (maxlimit < 0 || maxlimit > 255) return (PIX *)ERROR_PTR("invalid maxlimit", procName, NULL); if (satlimit < 1) return (PIX *)ERROR_PTR("invalid satlimit", procName, NULL); pixGetDimensions(pixs, &w, &h, NULL); datas = pixGetData(pixs); wpls = pixGetWpl(pixs); if ((pixd = pixCreate(w, h, 1)) == NULL) return (PIX *)ERROR_PTR("pixd not made", procName, NULL); datad = pixGetData(pixd); wpld = pixGetWpl(pixd); for (i = 0; i < h; i++) { lines = datas + i * wpls; lined = datad + i * wpld; for (j = 0; j < w; j++) { extractRGBValues(lines[j], &rval, &gval, &bval); minrg = L_MIN(rval, gval); min = L_MIN(minrg, bval); maxrg = L_MAX(rval, gval); max = L_MAX(maxrg, bval); sat = max - min; if (max <= maxlimit && sat <= satlimit) SET_DATA_BIT(lined, j); } } return pixd; } /* ----------------------------------------------------------------------- * * Generate a mask over pixels that have RGB color components * * within the prescribed range (a cube in RGB color space) * * ----------------------------------------------------------------------- */ /*! * \brief pixMaskOverColorRange() * * \param[in] pixs 32 bpp rgb or 8 bpp colormapped * \param[in] rmin, rmax min and max allowed values for red component * \param[in] gmin, gmax ditto for green * \param[in] bmin, bmax ditto for blue * \return pixd 1 bpp, mask over color pixels, or NULL on error */ PIX * pixMaskOverColorRange(PIX *pixs, l_int32 rmin, l_int32 rmax, l_int32 gmin, l_int32 gmax, l_int32 bmin, l_int32 bmax) { l_int32 w, h, d, i, j, wpls, wpld; l_int32 rval, gval, bval; l_uint32 *datas, *datad, *lines, *lined; PIX *pixc, *pixd; PIXCMAP *cmap; PROCNAME("pixMaskOverColorRange"); if (!pixs) return (PIX *)ERROR_PTR("pixs not defined", procName, NULL); pixGetDimensions(pixs, &w, &h, &d); cmap = pixGetColormap(pixs); if (!cmap && d != 32) return (PIX *)ERROR_PTR("pixs not cmapped or 32 bpp", procName, NULL); if (cmap) pixc = pixRemoveColormap(pixs, REMOVE_CMAP_TO_FULL_COLOR); else pixc = pixClone(pixs); pixd = pixCreate(w, h, 1); datad = pixGetData(pixd); wpld = pixGetWpl(pixd); datas = pixGetData(pixc); wpls = pixGetWpl(pixc); for (i = 0; i < h; i++) { lines = datas + i * wpls; lined = datad + i * wpld; for (j = 0; j < w; j++) { extractRGBValues(lines[j], &rval, &gval, &bval); if (rval < rmin || rval > rmax) continue; if (gval < gmin || gval > gmax) continue; if (bval < bmin || bval > bmax) continue; SET_DATA_BIT(lined, j); } } pixDestroy(&pixc); return pixd; } /* ----------------------------------------------------------------------- * * Determine if there are significant color regions in a page image * * ----------------------------------------------------------------------- */ /*! * \brief pixFindColorRegions() * * \param[in] pixs 32 bpp rgb * \param[in] pixm [optional] 1 bpp mask image * \param[in] factor subsample factor; integer >= 1 * \param[in] lightthresh threshold for component average in lightest * of 10 buckets; typ. 210; -1 for default * \param[in] darkthresh threshold to eliminate dark pixels (e.g., text) * from consideration; typ. 70; -1 for default. * \param[in] mindiff minimum difference (b - r) and (g - r), used to * find blue or green pixels; typ. 10; -1 for default * \param[in] colordiff minimum difference in (max - min) component to * qualify as a color pixel; typ. 90; -1 for default * \param[in] edgefract fraction of image half-width and half-height * for which color pixels are ignored; typ. 0.05. * \param[out] pcolorfract fraction of 'color' pixels found * \param[out] pcolormask1 [optional] mask over background color, if any * \param[out] pcolormask2 [optional] filtered mask over background color * \param[out] pixadb [optional] debug intermediate results * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) This function tries to determine if there is a significant
 *          color or darker region on a scanned page image, where part
 *          of the image is background that is either white or reddish.
 *          This also allows extraction of regions of colored pixels that
 *          have a smaller red component than blue or green components.
 *      (2) If %pixm exists, pixels under its fg are combined with
 *          dark pixels to make a mask of pixels not to be considered
 *          as color candidates.
 *      (3) There are four thresholds.
 *          * %lightthresh: compute the average value of each rgb pixel,
 *            and make 10 buckets by value.  If the lightest bucket gray
 *            value is below %lightthresh, the image is not considered
 *            to have a light bg, and this returns 0.0 for %colorfract.
 *          * %darkthresh: ignore pixels darker than this (typ. fg text).
 *            We make a 1 bpp mask of these pixels, and then dilate it to
 *            remove all vestiges of fg from their vicinity.
 *          * %mindiff: consider pixels with either (b - r) or (g - r)
 *            being at least this value, as having color.
 *          * %colordiff: consider pixels where the (max - min) difference
 *            of the pixel components exceeds this value, as having color.
 *      (4) All components of color pixels that are touching the image
 *          border are removed.  Additionally, all pixels within some
 *          normalized distance %edgefract from the image border can
 *          be removed.  This insures that dark pixels near the edge
 *          of the image are not included.
 *      (5) This returns in %pcolorfract the fraction of pixels that have
 *          color and are not in the set consisting of an OR between
 *          %pixm and the dilated dark pixel mask.
 *      (6) No masks are returned unless light color pixels are found.
 *          If colorfract > 0.0 and %pcolormask1 is defined, this returns
 *          a 1 bpp mask with fg pixels over the color background.
 *          This mask may have some holes in it.
 *      (7) If colorfract > 0.0 and %pcolormask2 is defined, this returns
 *          a version of colormask1 where small holes have been filled.
 *      (8) To generate a boxa of rectangular regions from the overlap
 *          of components in the filtered mask:
 *                boxa1 = pixConnCompBB(colormask2, 8);
 *                boxa2 = boxaCombineOverlaps(boxa1, NULL);
 *          This is done here in debug mode.
 * 
*/ l_ok pixFindColorRegions(PIX *pixs, PIX *pixm, l_int32 factor, l_int32 lightthresh, l_int32 darkthresh, l_int32 mindiff, l_int32 colordiff, l_float32 edgefract, l_float32 *pcolorfract, PIX **pcolormask1, PIX **pcolormask2, PIXA *pixadb) { l_int32 w, h, count, rval, gval, bval, aveval, proceed; l_float32 ratio; l_uint32 *carray; BOXA *boxa1, *boxa2; PIX *pix1, *pix2, *pix3, *pix4, *pix5, *pixm1, *pixm2, *pixm3; PROCNAME("pixFindColorRegions"); if (pcolormask1) *pcolormask1 = NULL; if (pcolormask2) *pcolormask2 = NULL; if (!pcolorfract) return ERROR_INT("&colorfract not defined", procName, 1); *pcolorfract = 0.0; if (!pixs || pixGetDepth(pixs) != 32) return ERROR_INT("pixs not defined or not 32 bpp", procName, 1); if (factor < 1) factor = 1; if (lightthresh < 0) lightthresh = 210; /* defaults */ if (darkthresh < 0) darkthresh = 70; if (mindiff < 0) mindiff = 10; if (colordiff < 0) colordiff = 90; if (edgefract < 0.0 || edgefract > 1.0) edgefract = 0.05f; /* Check if pixm covers most of the image. If so, just return. */ if (pixm) { pixForegroundFraction(pixm, &ratio); if (ratio > 0.7) { if (pixadb) L_INFO("pixm has big fg: %f5.2\n", procName, ratio); return 0; } } /* Get the light background color. Use the average component value * and select the lightest of 10 buckets. Require that it is * reddish and, using lightthresh, not too dark. */ pixGetRankColorArray(pixs, 10, L_SELECT_AVERAGE, factor, &carray, NULL, 0); if (!carray) return ERROR_INT("rank color array not made", procName, 1); extractRGBValues(carray[9], &rval, &gval, &bval); if (pixadb) L_INFO("lightest background color: (r,g,b) = (%d,%d,%d)\n", procName, rval, gval, bval); proceed = TRUE; if ((rval < bval - 2) || (rval < gval - 2)) { if (pixadb) L_INFO("background not reddish\n", procName); proceed = FALSE; } aveval = (rval + gval + bval) / 3; if (aveval < lightthresh) { if (pixadb) L_INFO("background too dark\n", procName); proceed = FALSE; } if (pixadb) { pix1 = pixDisplayColorArray(carray, 10, 120, 3, 6); pixaAddPix(pixadb, pix1, L_INSERT); } LEPT_FREE(carray); if (proceed == FALSE) return 0; /* Make a mask pixm1 over the dark pixels in the image: * convert to gray using the average of the components; * threshold using darkthresh; do a small dilation; * combine with pixm. */ pix1 = pixConvertRGBToGray(pixs, 0.33f, 0.34f, 0.33f); if (pixadb) pixaAddPix(pixadb, pix1, L_COPY); pixm1 = pixThresholdToBinary(pix1, darkthresh); pixDilateBrick(pixm1, pixm1, 7, 7); if (pixadb) pixaAddPix(pixadb, pixm1, L_COPY); if (pixm) { pixOr(pixm1, pixm1, pixm); if (pixadb) pixaAddPix(pixadb, pixm1, L_COPY); } pixDestroy(&pix1); /* Make masks over pixels that are bluish, or greenish, or have a very large color saturation (max - min) value. */ pixm2 = pixConvertRGBToBinaryArb(pixs, -1.0, 0.0, 1.0, mindiff, L_SELECT_IF_GTE); /* b - r */ if (pixadb) pixaAddPix(pixadb, pixm2, L_COPY); pix1 = pixConvertRGBToBinaryArb(pixs, -1.0, 1.0, 0.0, mindiff, L_SELECT_IF_GTE); /* g - r */ if (pixadb) pixaAddPix(pixadb, pix1, L_COPY); pixOr(pixm2, pixm2, pix1); pixDestroy(&pix1); pix1 = pixConvertRGBToGrayMinMax(pixs, L_CHOOSE_MAXDIFF); pix2 = pixThresholdToBinary(pix1, colordiff); pixInvert(pix2, pix2); if (pixadb) pixaAddPix(pixadb, pix2, L_COPY); pixOr(pixm2, pixm2, pix2); if (pixadb) pixaAddPix(pixadb, pixm2, L_COPY); pixDestroy(&pix1); pixDestroy(&pix2); /* Subtract the dark pixels represented by pixm1. * pixm2 now holds all the color pixels of interest */ pixSubtract(pixm2, pixm2, pixm1); pixDestroy(&pixm1); if (pixadb) pixaAddPix(pixadb, pixm2, L_COPY); /* But we're not quite finished. Remove pixels from any component * that is touching the image border. False color pixels can * sometimes be found there if the image is much darker near * the border, due to oxidation or reduced illumination. Also * remove any pixels within the normalized fraction %distfract * of the image border. */ pixm3 = pixRemoveBorderConnComps(pixm2, 8); pixGetDimensions(pixm3, &w, &h, NULL); pixDestroy(&pixm2); if (edgefract > 0.0) { pix2 = pixMakeSymmetricMask(w, h, edgefract, edgefract, L_USE_INNER); pixAnd(pixm3, pixm3, pix2); pixDestroy(&pix2); } if (pixadb) pixaAddPix(pixadb, pixm3, L_COPY); /* Get the fraction of light color pixels */ pixCountPixels(pixm3, &count, NULL); *pcolorfract = (l_float32)count / ((l_float32)(w) * h); if (pixadb) { if (count == 0) L_INFO("no light color pixels found\n", procName); else L_INFO("fraction of light color pixels = %5.3f\n", procName, *pcolorfract); } /* Debug: extract the color pixels from pixs */ if (pixadb && count > 0) { /* Use pixm3 to extract the color pixels */ pix3 = pixCreateTemplate(pixs); pixSetAll(pix3); pixCombineMasked(pix3, pixs, pixm3); pixaAddPix(pixadb, pix3, L_INSERT); /* Use additional filtering to extract the color pixels */ pix3 = pixCloseSafeBrick(NULL, pixm3, 15, 15); pixaAddPix(pixadb, pix3, L_INSERT); pix5 = pixCreateTemplate(pixs); pixSetAll(pix5); pixCombineMasked(pix5, pixs, pix3); pixaAddPix(pixadb, pix5, L_INSERT); /* Get the combined bounding boxes of the mask components * in pix3, and extract those pixels from pixs. */ boxa1 = pixConnCompBB(pix3, 8); boxa2 = boxaCombineOverlaps(boxa1, NULL); pix4 = pixCreateTemplate(pix3); pixMaskBoxa(pix4, pix4, boxa2, L_SET_PIXELS); pixaAddPix(pixadb, pix4, L_INSERT); pix5 = pixCreateTemplate(pixs); pixSetAll(pix5); pixCombineMasked(pix5, pixs, pix4); pixaAddPix(pixadb, pix5, L_INSERT); boxaDestroy(&boxa1); boxaDestroy(&boxa2); } pixaAddPix(pixadb, pixs, L_COPY); /* Optional colormask returns */ if (pcolormask2 && count > 0) *pcolormask2 = pixCloseSafeBrick(NULL, pixm3, 15, 15); if (pcolormask1 && count > 0) *pcolormask1 = pixm3; else pixDestroy(&pixm3); return 0; } /* ----------------------------------------------------------------------- * * Find the number of perceptually significant gray intensities * * in a grayscale image. * * ----------------------------------------------------------------------- */ /*! * \brief pixNumSignificantGrayColors() * * \param[in] pixs 8 bpp gray * \param[in] darkthresh dark threshold for minimum intensity to be * considered; typ. 20 * \param[in] lightthresh threshold near white, for maximum intensity * to be considered; typ. 236 * \param[in] minfract minimum fraction of all pixels to include a level * as significant; typ. 0.0001; should be < 0.001 * \param[in] factor subsample factor; integer >= 1 * \param[out] pncolors number of significant colors; 0 on error * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) This function is asking the question: how many perceptually
 *          significant gray color levels is in this pix?
 *          A color level must meet 3 criteria to be significant:
 *            ~ it can't be too close to black
 *            ~ it can't be too close to white
 *            ~ it must have at least some minimum fractional population
 *      (2) Use -1 for default values for darkthresh, lightthresh and minfract.
 *      (3) Choose default of darkthresh = 20, because variations in very
 *          dark pixels are not visually significant.
 *      (4) Choose default of lightthresh = 236, because document images
 *          that have been jpeg'd typically have near-white pixels in the
 *          8x8 jpeg blocks, and these should not be counted.  It is desirable
 *          to obtain a clean image by quantizing this noise away.
 * 
*/ l_ok pixNumSignificantGrayColors(PIX *pixs, l_int32 darkthresh, l_int32 lightthresh, l_float32 minfract, l_int32 factor, l_int32 *pncolors) { l_int32 i, w, h, count, mincount, ncolors; NUMA *na; PROCNAME("pixNumSignificantGrayColors"); if (!pncolors) return ERROR_INT("&ncolors not defined", procName, 1); *pncolors = 0; if (!pixs || pixGetDepth(pixs) != 8) return ERROR_INT("pixs not defined or not 8 bpp", procName, 1); if (darkthresh < 0) darkthresh = 20; /* defaults */ if (lightthresh < 0) lightthresh = 236; if (minfract < 0.0) minfract = 0.0001f; if (minfract > 1.0) return ERROR_INT("minfract > 1.0", procName, 1); if (minfract >= 0.001) L_WARNING("minfract too big; likely to underestimate ncolors\n", procName); if (lightthresh > 255 || darkthresh >= lightthresh) return ERROR_INT("invalid thresholds", procName, 1); if (factor < 1) factor = 1; pixGetDimensions(pixs, &w, &h, NULL); mincount = (l_int32)(minfract * w * h * factor * factor); if ((na = pixGetGrayHistogram(pixs, factor)) == NULL) return ERROR_INT("na not made", procName, 1); ncolors = 2; /* add in black and white */ for (i = darkthresh; i <= lightthresh; i++) { numaGetIValue(na, i, &count); if (count >= mincount) ncolors++; } *pncolors = ncolors; numaDestroy(&na); return 0; } /* ----------------------------------------------------------------------- * * Identifies images where color quantization will cause posterization * * due to the existence of many colors in low-gradient regions. * * ----------------------------------------------------------------------- */ /*! * \brief pixColorsForQuantization() * \param[in] pixs 8 bpp gray or 32 bpp rgb; with or without colormap * \param[in] thresh binary threshold on edge gradient; 0 for default * \param[out] pncolors the number of colors found * \param[out] piscolor [optional] 1 if significant color is found; * 0 otherwise. If pixs is 8 bpp, and does not have * a colormap with color entries, this is 0 * \param[in] debug 1 to output masked image that is tested for colors; * 0 otherwise * \return 0 if OK, 1 on error. * *
 * Notes:
 *      (1) This function finds a measure of the number of colors that are
 *          found in low-gradient regions of an image.  By its
 *          magnitude relative to some threshold (not specified in
 *          this function), it gives a good indication of whether
 *          quantization will generate posterization.   This number
 *          is larger for images with regions of slowly varying
 *          intensity (if 8 bpp) or color (if rgb). Such images, if
 *          quantized, may require dithering to avoid posterization,
 *          and lossless compression is then expected to be poor.
 *      (2) If pixs has a colormap, the number of colors returned is
 *          the number in the colormap.
 *      (3) It is recommended that document images be reduced to a width
 *          of 800 pixels before applying this function.  Then it can
 *          be expected that color detection will be fairly accurate
 *          and the number of colors will reflect both the content and
 *          the type of compression to be used.  For less than 15 colors,
 *          there is unlikely to be a halftone image, and lossless
 *          quantization should give both a good visual result and
 *          better compression.
 *      (4) When using the default threshold on the gradient (15),
 *          images (both gray and rgb) where ncolors is greater than
 *          about 15 will compress poorly with either lossless
 *          compression or dithered quantization, and they may be
 *          posterized with non-dithered quantization.
 *      (5) For grayscale images, or images without significant color,
 *          this returns the number of significant gray levels in
 *          the low-gradient regions.  The actual number of gray levels
 *          can be large due to jpeg compression noise in the background.
 *      (6) Similarly, for color images, the actual number of different
 *          (r,g,b) colors in the low-gradient regions (rather than the
 *          number of occupied level 4 octcubes) can be quite large, e.g.,
 *          due to jpeg compression noise, even for regions that appear
 *          to be of a single color.  By quantizing to level 4 octcubes,
 *          most of these superfluous colors are removed from the counting.
 *      (7) The image is tested for color.  If there is very little color,
 *          it is thresholded to gray and the number of gray levels in
 *          the low gradient regions is found.  If the image has color,
 *          the number of occupied level 4 octcubes is found.
 *      (8) The number of colors in the low-gradient regions increases
 *          monotonically with the threshold %thresh on the edge gradient.
 *      (9) Background: grayscale and color quantization is often useful
 *          to achieve highly compressed images with little visible
 *          distortion.  However, gray or color washes (regions of
 *          low gradient) can defeat this approach to high compression.
 *          How can one determine if an image is expected to compress
 *          well using gray or color quantization?  We use the fact that
 *            * gray washes, when quantized with less than 50 intensities,
 *              have posterization (visible boundaries between regions
 *              of uniform 'color') and poor lossless compression
 *            * color washes, when quantized with level 4 octcubes,
 *              typically result in both posterization and the occupancy
 *              of many level 4 octcubes.
 *          Images can have colors either intrinsically or as jpeg
 *          compression artifacts.  This function reduces but does not
 *          completely eliminate measurement of jpeg quantization noise
 *          in the white background of grayscale or color images.
 * 
*/ l_ok pixColorsForQuantization(PIX *pixs, l_int32 thresh, l_int32 *pncolors, l_int32 *piscolor, l_int32 debug) { l_int32 w, h, d, minside, factor; l_float32 pixfract, colorfract; PIX *pixt, *pixsc, *pixg, *pixe, *pixb, *pixm; PIXCMAP *cmap; PROCNAME("pixColorsForQuantization"); if (piscolor) *piscolor = 0; if (!pncolors) return ERROR_INT("&ncolors not defined", procName, 1); *pncolors = 0; if (!pixs) return ERROR_INT("pixs not defined", procName, 1); if ((cmap = pixGetColormap(pixs)) != NULL) { *pncolors = pixcmapGetCount(cmap); if (piscolor) pixcmapHasColor(cmap, piscolor); return 0; } pixGetDimensions(pixs, &w, &h, &d); if (d != 8 && d != 32) return ERROR_INT("pixs not 8 or 32 bpp", procName, 1); if (thresh <= 0) thresh = 15; /* First test if 32 bpp has any significant color; if not, * convert it to gray. Colors whose average values are within * 20 of black or 8 of white are ignored because they're not * very 'colorful'. If less than 2.5/10000 of the pixels have * significant color, consider the image to be gray. */ minside = L_MIN(w, h); if (d == 8) { pixt = pixClone(pixs); } else { /* d == 32 */ factor = L_MAX(1, minside / 400); pixColorFraction(pixs, 20, 248, 30, factor, &pixfract, &colorfract); if (pixfract * colorfract < 0.00025) { pixt = pixGetRGBComponent(pixs, COLOR_RED); d = 8; } else { /* d == 32 */ pixt = pixClone(pixs); if (piscolor) *piscolor = 1; } } /* If the smallest side is less than 1000, do not downscale. * If it is in [1000 ... 2000), downscale by 2x. If it is >= 2000, * downscale by 4x. Factors of 2 are chosen for speed. The * actual resolution at which subsequent calculations take place * is not strongly dependent on downscaling. */ factor = L_MAX(1, minside / 500); if (factor == 1) pixsc = pixCopy(NULL, pixt); /* to be sure pixs is unchanged */ else if (factor == 2 || factor == 3) pixsc = pixScaleAreaMap2(pixt); else pixsc = pixScaleAreaMap(pixt, 0.25, 0.25); /* Basic edge mask generation procedure: * ~ work on a grayscale image * ~ get a 1 bpp edge mask by using an edge filter and * thresholding to get fg pixels at the edges * ~ for gray, dilate with a 3x3 brick Sel to get mask over * all pixels within a distance of 1 pixel from the nearest * edge pixel * ~ for color, dilate with a 7x7 brick Sel to get mask over * all pixels within a distance of 3 pixels from the nearest * edge pixel */ if (d == 8) pixg = pixClone(pixsc); else /* d == 32 */ pixg = pixConvertRGBToLuminance(pixsc); pixe = pixSobelEdgeFilter(pixg, L_ALL_EDGES); pixb = pixThresholdToBinary(pixe, thresh); pixInvert(pixb, pixb); if (d == 8) pixm = pixMorphSequence(pixb, "d3.3", 0); else pixm = pixMorphSequence(pixb, "d7.7", 0); /* Mask the near-edge pixels to white, and count the colors. * If grayscale, don't count colors within 20 levels of * black or white, and only count colors with a fraction * of at least 1/10000 of the image pixels. * If color, count the number of level 4 octcubes that * contain at least 20 pixels. These magic numbers are guesses * as to what might work, based on a small data set. Results * should not be overly sensitive to their actual values. */ if (d == 8) { pixSetMasked(pixg, pixm, 0xff); if (debug) pixWrite("junkpix8.png", pixg, IFF_PNG); pixNumSignificantGrayColors(pixg, 20, 236, 0.0001f, 1, pncolors); } else { /* d == 32 */ pixSetMasked(pixsc, pixm, 0xffffffff); if (debug) pixWrite("junkpix32.png", pixsc, IFF_PNG); pixNumberOccupiedOctcubes(pixsc, 4, 20, -1, pncolors); } pixDestroy(&pixt); pixDestroy(&pixsc); pixDestroy(&pixg); pixDestroy(&pixe); pixDestroy(&pixb); pixDestroy(&pixm); return 0; } /* ----------------------------------------------------------------------- * * Find the number of unique colors in an image * * ----------------------------------------------------------------------- */ /*! * \brief pixNumColors() * \param[in] pixs 2, 4, 8, 32 bpp * \param[in] factor subsampling factor; integer * \param[out] pncolors the number of colors found in the pix * \return 0 if OK, 1 on error. * *
 * Notes:
 *      (1) This returns the number of colors found in the image,
 *          even if there is a colormap.  If %factor == 1 and the
 *          number of colors differs from the number of entries
 *          in the colormap, a warning is issued.
 *      (2) Use %factor == 1 to find the actual number of colors.
 *          Use %factor > 1 to more efficiently find an approximate
 *          number of colors.
 *      (3) For d = 2, 4 or 8 bpp grayscale, this returns the number
 *          of colors found in the image in 'ncolors'.
 *      (4) For d = 32 bpp (rgb), if the number of colors is greater
 *          than 256, this uses a hash set with %factor == 1.
 * 
*/ l_ok pixNumColors(PIX *pixs, l_int32 factor, l_int32 *pncolors) { l_int32 w, h, d, i, j, wpl, hashsize, sum, count, manycolors; l_int32 rval, gval, bval, val; l_int32 *inta; l_uint32 pixel; l_uint32 *data, *line; PIXCMAP *cmap; PROCNAME("pixNumColors"); if (!pncolors) return ERROR_INT("&ncolors not defined", procName, 1); *pncolors = 0; if (!pixs) return ERROR_INT("pixs not defined", procName, 1); pixGetDimensions(pixs, &w, &h, &d); if (d != 2 && d != 4 && d != 8 && d != 32) return ERROR_INT("d not in {2, 4, 8, 32}", procName, 1); if (factor < 1) factor = 1; data = pixGetData(pixs); wpl = pixGetWpl(pixs); sum = 0; if (d != 32) { /* grayscale */ inta = (l_int32 *)LEPT_CALLOC(256, sizeof(l_int32)); for (i = 0; i < h; i += factor) { line = data + i * wpl; for (j = 0; j < w; j += factor) { if (d == 8) val = GET_DATA_BYTE(line, j); else if (d == 4) val = GET_DATA_QBIT(line, j); else /* d == 2 */ val = GET_DATA_DIBIT(line, j); inta[val] = 1; } } for (i = 0; i < 256; i++) if (inta[i]) sum++; *pncolors = sum; LEPT_FREE(inta); cmap = pixGetColormap(pixs); if (cmap && factor == 1) { count = pixcmapGetCount(cmap); if (sum != count) L_WARNING("colormap size %d differs from actual colors\n", procName, count); } return 0; } /* 32 bpp rgb; quit if we get above 256 colors */ hashsize = 5507; /* big and prime; collisions are not likely */ inta = (l_int32 *)LEPT_CALLOC(hashsize, sizeof(l_int32)); manycolors = 0; for (i = 0; i < h && manycolors == 0; i += factor) { line = data + i * wpl; for (j = 0; j < w; j += factor) { pixel = line[j]; extractRGBValues(pixel, &rval, &gval, &bval); val = (137 * rval + 269 * gval + 353 * bval) % hashsize; if (inta[val] == 0) { inta[val] = 1; sum++; if (sum > 256) { manycolors = 1; break; } } } } LEPT_FREE(inta); if (manycolors == 0) { *pncolors = sum; return 0; } /* More than 256 colors in RGB image; count all the pixels */ return pixCountRGBColorsByHash(pixs, pncolors); } /* ----------------------------------------------------------------------- * * Lossless conversion of RGB image to colormapped * * ----------------------------------------------------------------------- */ /*! * \brief pixConvertRGBToCmapLossless() * \param[in] pixs 32 bpp RGB * \return pixd if num colors <= 256; null otherwise or on error * *
 * Notes:
 *      (1) If there are not more than 256 colors, this losslessly
 *          converts and RGB image to a colormapped one, with the
 *          smallest pixel depth required to hold all the colors.
 * 
*/ PIX * pixConvertRGBToCmapLossless(PIX *pixs) { l_int32 w, h, d, i, j, wpls, wpld, hashsize, hashval, ncolors, index; l_int32 rval, gval, bval, val; l_int32 *hasha1, *hasha2; l_uint32 pixel; l_uint32 *datas, *lines, *datad, *lined; PIX *pixd; PIXCMAP *cmap; PROCNAME("pixConvertRGBToCmapLossless"); if (!pixs || pixGetDepth(pixs) != 32) return (PIX *)ERROR_PTR("pixs undefined or not 32 bpp", procName, NULL); pixNumColors(pixs, 1, &ncolors); if (ncolors > 256) { L_ERROR("too many colors found: %d\n", procName, ncolors); return NULL; } pixGetDimensions(pixs, &w, &h, NULL); if (ncolors <= 2) d = 1; else if (ncolors <= 4) d = 2; else if (ncolors <= 16) d = 4; else /* ncolors <= 256 */ d = 8; if ((pixd = pixCreate(w, h, d)) == NULL) return (PIX *)ERROR_PTR("pixd not made", procName, NULL); cmap = pixcmapCreate(d); datas = pixGetData(pixs); wpls = pixGetWpl(pixs); datad = pixGetData(pixd); wpld = pixGetWpl(pixd); /* hasha1 is a 1/0 indicator array for colors seen. hasha2 holds the index into the colormap that will be generated from the colors in the order seen. This is the value inserted into pixd. */ hashsize = 5507; /* big and prime; collisions are not likely */ hasha1 = (l_int32 *)LEPT_CALLOC(hashsize, sizeof(l_int32)); hasha2 = (l_int32 *)LEPT_CALLOC(hashsize, sizeof(l_int32)); index = -1; for (i = 0; i < h; i++) { lines = datas + i * wpls; lined = datad + i * wpld; for (j = 0; j < w; j++) { pixel = lines[j]; extractRGBValues(pixel, &rval, &gval, &bval); hashval = (137 * rval + 269 * gval + 353 * bval) % hashsize; if (hasha1[hashval] == 0) { /* new color */ hasha1[hashval] = 1; index++; hasha2[hashval] = index; pixcmapAddColor(cmap, rval, gval, bval); } val = hasha2[hashval]; setLineDataVal(lined, j, d, val); } } pixSetColormap(pixd, cmap); LEPT_FREE(hasha1); LEPT_FREE(hasha2); return pixd; } /* ----------------------------------------------------------------------- * * Find the most "populated" colors in the image (and quantize) * * ----------------------------------------------------------------------- */ /*! * \brief pixGetMostPopulatedColors() * \param[in] pixs 32 bpp rgb * \param[in] sigbits 2-6, significant bits retained in the quantizer * for each component of the input image * \param[in] factor subsampling factor; use 1 for no subsampling * \param[in] ncolors the number of most populated colors to select * \param[out] parray [optional] array of colors, each as 0xrrggbb00 * \param[out] pcmap [optional] colormap of the colors * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) This finds the %ncolors most populated cubes in rgb colorspace,
 *          where the cube size depends on %sigbits as
 *               cube side = (256 >> sigbits)
 *      (2) The rgb color components are found at the center of the cube.
 *      (3) The output array of colors can be displayed using
 *               pixDisplayColorArray(array, ncolors, ...);
 * 
*/ l_ok pixGetMostPopulatedColors(PIX *pixs, l_int32 sigbits, l_int32 factor, l_int32 ncolors, l_uint32 **parray, PIXCMAP **pcmap) { l_int32 n, i, rgbindex, rval, gval, bval; NUMA *nahisto, *naindex; PROCNAME("pixGetMostPopulatedColors"); if (!parray && !pcmap) return ERROR_INT("no return val requested", procName, 1); if (parray) *parray = NULL; if (pcmap) *pcmap = NULL; if (!pixs || pixGetDepth(pixs) != 32) return ERROR_INT("pixs not defined", procName, 1); if (sigbits < 2 || sigbits > 6) return ERROR_INT("sigbits not in [2 ... 6]", procName, 1); if (factor < 1 || ncolors < 1) return ERROR_INT("factor < 1 or ncolors < 1", procName, 1); if ((nahisto = pixGetRGBHistogram(pixs, sigbits, factor)) == NULL) return ERROR_INT("nahisto not made", procName, 1); /* naindex contains the index into nahisto, which is the rgbindex */ naindex = numaSortIndexAutoSelect(nahisto, L_SORT_DECREASING); numaDestroy(&nahisto); if (!naindex) return ERROR_INT("naindex not made", procName, 1); n = numaGetCount(naindex); ncolors = L_MIN(n, ncolors); if (parray) *parray = (l_uint32 *)LEPT_CALLOC(ncolors, sizeof(l_uint32)); if (pcmap) *pcmap = pixcmapCreate(8); for (i = 0; i < ncolors; i++) { numaGetIValue(naindex, i, &rgbindex); /* rgb index */ getRGBFromIndex(rgbindex, sigbits, &rval, &gval, &bval); if (parray) composeRGBPixel(rval, gval, bval, *parray + i); if (pcmap) pixcmapAddColor(*pcmap, rval, gval, bval); } numaDestroy(&naindex); return 0; } /*! * \brief pixSimpleColorQuantize() * \param[in] pixs 32 bpp rgb * \param[in] sigbits 2-4, significant bits retained in the quantizer * for each component of the input image * \param[in] factor subsampling factor; use 1 for no subsampling * \param[in] ncolors the number of most populated colors to select * \return pixd 8 bpp cmapped or NULL on error * *
 * Notes:
 *      (1) If you want to do color quantization for real, use octcube
 *          or modified median cut.  This function shows that it is
 *          easy to make a simple quantizer based solely on the population
 *          in cells of a given size in rgb color space.
 *      (2) The %ncolors most populated cells at the %sigbits level form
 *          the colormap for quantizing, and this uses octcube indexing
 *          under the covers to assign each pixel to the nearest color.
 *      (3) %sigbits is restricted to 2, 3 and 4.  At the low end, the
 *          color discrimination is very crude; at the upper end, a set of
 *          similar colors can dominate the result.  Interesting results
 *          are generally found for %sigbits = 3 and ncolors ~ 20.
 *      (4) See also pixColorSegment() for a method of quantizing the
 *          colors to generate regions of similar color.
 *      (5) See also pixConvertRGBToCmapLossless() to losslessly convert
 *          an RGB image with not more than 256 colors.
 * 
*/ PIX * pixSimpleColorQuantize(PIX *pixs, l_int32 sigbits, l_int32 factor, l_int32 ncolors) { l_int32 w, h; PIX *pixd; PIXCMAP *cmap; PROCNAME("pixSimpleColorQuantize"); if (!pixs || pixGetDepth(pixs) != 32) return (PIX *)ERROR_PTR("pixs not defined", procName, NULL); if (sigbits < 2 || sigbits > 4) return (PIX *)ERROR_PTR("sigbits not in {2,3,4}", procName, NULL); pixGetMostPopulatedColors(pixs, sigbits, factor, ncolors, NULL, &cmap); pixGetDimensions(pixs, &w, &h, NULL); pixd = pixCreate(w, h, 8); pixSetColormap(pixd, cmap); pixAssignToNearestColor(pixd, pixs, NULL, 4, NULL); return pixd; } /* ----------------------------------------------------------------------- * * Constructs a color histogram based on rgb indices * * ----------------------------------------------------------------------- */ /*! * \brief pixGetRGBHistogram() * \param[in] pixs 32 bpp rgb * \param[in] sigbits 2-6, significant bits retained in the quantizer * for each component of the input image * \param[in] factor subsampling factor; use 1 for no subsampling * \return numa histogram of colors, indexed by RGB * components, or NULL on error * *
 * Notes:
 *      (1) This uses a simple, fast method of indexing into an rgb image.
 *      (2) The output is a 1D histogram of count vs. rgb-index, which
 *          uses red sigbits as the most significant and blue as the least.
 *      (3) This function produces the same result as pixMedianCutHisto().
 * 
*/ NUMA * pixGetRGBHistogram(PIX *pixs, l_int32 sigbits, l_int32 factor) { l_int32 w, h, i, j, size, wpl, rval, gval, bval, npts; l_uint32 val32, rgbindex; l_float32 *array; l_uint32 *data, *line, *rtab, *gtab, *btab; NUMA *na; PROCNAME("pixGetRGBHistogram"); if (!pixs || pixGetDepth(pixs) != 32) return (NUMA *)ERROR_PTR("pixs not defined", procName, NULL); if (sigbits < 2 || sigbits > 6) return (NUMA *)ERROR_PTR("sigbits not in [2 ... 6]", procName, NULL); if (factor < 1) return (NUMA *)ERROR_PTR("factor < 1", procName, NULL); /* Get histogram size: 2^(3 * sigbits) */ size = 1 << (3 * sigbits); /* 64, 512, 4096, 32768, 262144 */ na = numaMakeConstant(0, size); /* init to all 0 */ array = numaGetFArray(na, L_NOCOPY); makeRGBIndexTables(&rtab, >ab, &btab, sigbits); /* Check the number of sampled pixels */ pixGetDimensions(pixs, &w, &h, NULL); npts = ((w + factor - 1) / factor) * ((h + factor - 1) / factor); if (npts < 1000) L_WARNING("only sampling %d pixels\n", procName, npts); wpl = pixGetWpl(pixs); data = pixGetData(pixs); for (i = 0; i < h; i += factor) { line = data + i * wpl; for (j = 0; j < w; j += factor) { val32 = *(line + j); extractRGBValues(val32, &rval, &gval, &bval); rgbindex = rtab[rval] | gtab[gval] | btab[bval]; array[rgbindex]++; } } LEPT_FREE(rtab); LEPT_FREE(gtab); LEPT_FREE(btab); return na; } /*! * \brief makeRGBIndexTables() * * \param[out] prtab, pgtab, pbtab 256-entry rgb index tables * \param[in] sigbits 2-6, significant bits retained in the quantizer * for each component of the input image * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) These tables are used to map from rgb sample values to
 *          an rgb index, using
 *             rgbindex = rtab[rval] | gtab[gval] | btab[bval]
 *          where, e.g., if sigbits = 3, the index is a 9 bit integer:
 *             r7 r6 r5 g7 g6 g5 b7 b6 b5
 * 
*/ l_ok makeRGBIndexTables(l_uint32 **prtab, l_uint32 **pgtab, l_uint32 **pbtab, l_int32 sigbits) { l_int32 i; l_uint32 *rtab, *gtab, *btab; PROCNAME("makeRGBIndexTables"); if (prtab) *prtab = NULL; if (pgtab) *pgtab = NULL; if (pbtab) *pbtab = NULL; if (!prtab || !pgtab || !pbtab) return ERROR_INT("not all table ptrs defined", procName, 1); if (sigbits < 2 || sigbits > 6) return ERROR_INT("sigbits not in [2 ... 6]", procName, 1); rtab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32)); gtab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32)); btab = (l_uint32 *)LEPT_CALLOC(256, sizeof(l_uint32)); if (!rtab || !gtab || !btab) return ERROR_INT("calloc fail for tab", procName, 1); *prtab = rtab; *pgtab = gtab; *pbtab = btab; switch (sigbits) { case 2: for (i = 0; i < 256; i++) { rtab[i] = (i & 0xc0) >> 2; gtab[i] = (i & 0xc0) >> 4; btab[i] = (i & 0xc0) >> 6; } break; case 3: for (i = 0; i < 256; i++) { rtab[i] = (i & 0xe0) << 1; gtab[i] = (i & 0xe0) >> 2; btab[i] = (i & 0xe0) >> 5; } break; case 4: for (i = 0; i < 256; i++) { rtab[i] = (i & 0xf0) << 4; gtab[i] = (i & 0xf0); btab[i] = (i & 0xf0) >> 4; } break; case 5: for (i = 0; i < 256; i++) { rtab[i] = (i & 0xf8) << 7; gtab[i] = (i & 0xf8) << 2; btab[i] = (i & 0xf8) >> 3; } break; case 6: for (i = 0; i < 256; i++) { rtab[i] = (i & 0xfc) << 10; gtab[i] = (i & 0xfc) << 4; btab[i] = (i & 0xfc) >> 2; } break; default: L_ERROR("Illegal sigbits = %d\n", procName, sigbits); return ERROR_INT("sigbits not in [2 ... 6]", procName, 1); } return 0; } /*! * \brief getRGBFromIndex() * * \param[in] index rgbindex * \param[in] sigbits 2-6, significant bits retained in the quantizer * for each component of the input image * \param[out] prval, pgval, pbval rgb values * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) The %index is expressed in bits, based on the the
 *          %sigbits of the r, g and b components, as
 *             r7 r6 ... g7 g6 ... b7 b6 ...
 *      (2) The computed rgb values are in the center of the quantized cube.
 *          The extra bit that is OR'd accomplishes this.
 * 
*/ l_ok getRGBFromIndex(l_uint32 index, l_int32 sigbits, l_int32 *prval, l_int32 *pgval, l_int32 *pbval) { PROCNAME("getRGBFromIndex"); if (prval) *prval = 0; if (pgval) *pgval = 0; if (pbval) *pbval = 0; if (!prval || !pgval || !pbval) return ERROR_INT("not all component ptrs defined", procName, 1); if (sigbits < 2 || sigbits > 6) return ERROR_INT("sigbits not in [2 ... 6]", procName, 1); switch (sigbits) { case 2: *prval = ((index << 2) & 0xc0) | 0x20; *pgval = ((index << 4) & 0xc0) | 0x20; *pbval = ((index << 6) & 0xc0) | 0x20; break; case 3: *prval = ((index >> 1) & 0xe0) | 0x10; *pgval = ((index << 2) & 0xe0) | 0x10; *pbval = ((index << 5) & 0xe0) | 0x10; break; case 4: *prval = ((index >> 4) & 0xf0) | 0x08; *pgval = (index & 0xf0) | 0x08; *pbval = ((index << 4) & 0xf0) | 0x08; break; case 5: *prval = ((index >> 7) & 0xf8) | 0x04; *pgval = ((index >> 2) & 0xf8) | 0x04; *pbval = ((index << 3) & 0xf8) | 0x04; break; case 6: *prval = ((index >> 10) & 0xfc) | 0x02; *pgval = ((index >> 4) & 0xfc) | 0x02; *pbval = ((index << 2) & 0xfc) | 0x02; break; default: L_ERROR("Illegal sigbits = %d\n", procName, sigbits); return ERROR_INT("sigbits not in [2 ... 6]", procName, 1); } return 0; } /* ----------------------------------------------------------------------- * * Identify images that have highlight (red) color * * ----------------------------------------------------------------------- */ /*! * \brief pixHasHighlightRed() * * \param[in] pixs 32 bpp rgb * \param[in] factor subsampling; an integer >= 1; use 1 for all pixels * \param[in] minfract threshold fraction of all image pixels; must be > 0.0 * \param[in] fthresh threshold on a function of the components; typ. ~2.5 * \param[out] phasred 1 if red pixels are above threshold * \param[out] pratio [optional] normalized fraction of threshold * red pixels that is actually observed * \param[out] ppixdb [optional] seed pixel mask * \return 0 if OK, 1 on error * *
 * Notes:
 *      (1) Pixels are identified as red if they satisfy two conditions:
 *          (a) The components satisfy (R-B)/B > %fthresh   (red or dark fg)
 *          (b) The red component satisfied R > 128  (red or light bg)
 *          Masks are generated for (a) and (b), and the intersection
 *          gives the pixels that are red but not either light bg or
 *          dark fg.
 *      (2) A typical value for minfract = 0.0001, which gives sensitivity
 *          to an image where a small fraction of the pixels are printed
 *          in red.
 *      (3) A typical value for fthresh = 2.5.  Higher values give less
 *          sensitivity to red, and fewer false positives.
 * 
*/ l_ok pixHasHighlightRed(PIX *pixs, l_int32 factor, l_float32 minfract, l_float32 fthresh, l_int32 *phasred, l_float32 *pratio, PIX **ppixdb) { l_float32 fract, ratio; PIX *pix1, *pix2, *pix3, *pix4; FPIX *fpix; PROCNAME("pixHasHighlightRed"); if (pratio) *pratio = 0.0; if (ppixdb) *ppixdb = NULL; if (phasred) *phasred = 0; if (!pratio && !ppixdb) return ERROR_INT("no return val requested", procName, 1); if (!phasred) return ERROR_INT("&hasred not defined", procName, 1); if (!pixs || pixGetDepth(pixs) != 32) return ERROR_INT("pixs not defined or not 32 bpp", procName, 1); if (minfract <= 0.0) return ERROR_INT("minfract must be > 0.0", procName, 1); if (fthresh < 1.5 || fthresh > 3.5) L_WARNING("fthresh = %f is out of normal bounds\n", procName, fthresh); if (factor > 1) pix1 = pixScaleByIntSampling(pixs, factor); else pix1 = pixClone(pixs); /* Identify pixels that are either red or dark foreground */ fpix = pixComponentFunction(pix1, 1.0, 0.0, -1.0, 0.0, 0.0, 1.0); pix2 = fpixThresholdToPix(fpix, fthresh); pixInvert(pix2, pix2); /* Identify pixels that are either red or light background */ pix3 = pixGetRGBComponent(pix1, COLOR_RED); pix4 = pixThresholdToBinary(pix3, 130); pixInvert(pix4, pix4); pixAnd(pix4, pix4, pix2); pixForegroundFraction(pix4, &fract); ratio = fract / minfract; L_INFO("fract = %7.5f, ratio = %7.3f\n", procName, fract, ratio); if (pratio) *pratio = ratio; if (ratio >= 1.0) *phasred = 1; if (ppixdb) *ppixdb = pix4; else pixDestroy(&pix4); pixDestroy(&pix1); pixDestroy(&pix2); pixDestroy(&pix3); fpixDestroy(&fpix); return 0; }