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Leptonica
1.82.0
Image processing and image analysis suite
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#include "allheaders.h"
Go to the source code of this file.
Functions | |
l_ok | pixColorContent (PIX *pixs, l_int32 rref, l_int32 gref, l_int32 bref, l_int32 mingray, PIX **ppixr, PIX **ppixg, PIX **ppixb) |
PIX * | pixColorMagnitude (PIX *pixs, l_int32 rref, l_int32 gref, l_int32 bref, l_int32 type) |
l_ok | pixColorFraction (PIX *pixs, l_int32 darkthresh, l_int32 lightthresh, l_int32 diffthresh, l_int32 factor, l_float32 *ppixfract, l_float32 *pcolorfract) |
PIX * | pixColorShiftWhitePoint (PIX *pixs, l_int32 rref, l_int32 gref, l_int32 bref) |
PIX * | pixMaskOverColorPixels (PIX *pixs, l_int32 threshdiff, l_int32 mindist) |
PIX * | pixMaskOverGrayPixels (PIX *pixs, l_int32 maxlimit, l_int32 satlimit) |
PIX * | pixMaskOverColorRange (PIX *pixs, l_int32 rmin, l_int32 rmax, l_int32 gmin, l_int32 gmax, l_int32 bmin, l_int32 bmax) |
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_ok | pixNumSignificantGrayColors (PIX *pixs, l_int32 darkthresh, l_int32 lightthresh, l_float32 minfract, l_int32 factor, l_int32 *pncolors) |
l_ok | pixColorsForQuantization (PIX *pixs, l_int32 thresh, l_int32 *pncolors, l_int32 *piscolor, l_int32 debug) |
l_ok | pixNumColors (PIX *pixs, l_int32 factor, l_int32 *pncolors) |
PIX * | pixConvertRGBToCmapLossless (PIX *pixs) |
l_ok | pixGetMostPopulatedColors (PIX *pixs, l_int32 sigbits, l_int32 factor, l_int32 ncolors, l_uint32 **parray, PIXCMAP **pcmap) |
PIX * | pixSimpleColorQuantize (PIX *pixs, l_int32 sigbits, l_int32 factor, l_int32 ncolors) |
NUMA * | pixGetRGBHistogram (PIX *pixs, l_int32 sigbits, l_int32 factor) |
l_ok | makeRGBIndexTables (l_uint32 **prtab, l_uint32 **pgtab, l_uint32 **pbtab, l_int32 sigbits) |
l_ok | getRGBFromIndex (l_uint32 index, l_int32 sigbits, l_int32 *prval, l_int32 *pgval, l_int32 *pbval) |
l_ok | pixHasHighlightRed (PIX *pixs, l_int32 factor, l_float32 minfract, l_float32 fthresh, l_int32 *phasred, l_float32 *pratio, PIX **ppixdb) |
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 <..>.
Definition in file colorcontent.c.
l_ok getRGBFromIndex | ( | l_uint32 | index, |
l_int32 | sigbits, | ||
l_int32 * | prval, | ||
l_int32 * | pgval, | ||
l_int32 * | pbval | ||
) |
[in] | index | rgbindex |
[in] | sigbits | 2-6, significant bits retained in the quantizer for each component of the input image |
[out] | prval,pgval,pbval | rgb values |
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.
Definition at line 1909 of file colorcontent.c.
l_ok makeRGBIndexTables | ( | l_uint32 ** | prtab, |
l_uint32 ** | pgtab, | ||
l_uint32 ** | pbtab, | ||
l_int32 | sigbits | ||
) |
[out] | prtab,pgtab,pbtab | 256-entry rgb index tables |
[in] | sigbits | 2-6, significant bits retained in the quantizer for each component of the input image |
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
Definition at line 1819 of file colorcontent.c.
l_ok pixColorContent | ( | PIX * | pixs, |
l_int32 | rref, | ||
l_int32 | gref, | ||
l_int32 | bref, | ||
l_int32 | mingray, | ||
PIX ** | ppixr, | ||
PIX ** | ppixg, | ||
PIX ** | ppixb | ||
) |
[in] | pixs | 32 bpp rgb or 8 bpp colormapped |
[in] | rref | reference value for red component |
[in] | gref | reference value for green component |
[in] | bref | reference value for blue component |
[in] | mingray | min gray value for which color is measured |
[out] | ppixr | [optional] 8 bpp red 'content' |
[out] | ppixg | [optional] 8 bpp green 'content' |
[out] | ppixb | [optional] 8 bpp blue 'content' |
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.
Definition at line 202 of file colorcontent.c.
References CCBorda::h, pixColorShiftWhitePoint(), pixCreate(), pixGetData(), pixGetDimensions(), and CCBorda::w.
l_ok pixColorFraction | ( | PIX * | pixs, |
l_int32 | darkthresh, | ||
l_int32 | lightthresh, | ||
l_int32 | diffthresh, | ||
l_int32 | factor, | ||
l_float32 * | ppixfract, | ||
l_float32 * | pcolorfract | ||
) |
[in] | pixs | 32 bpp rgb |
[in] | darkthresh | threshold near black; if the largest (lightest) component is below this, the pixel is not considered in the statistics; typ. 20 |
[in] | lightthresh | threshold near white; if the smallest (darkest) component is above this, the pixel is not considered in the statistics; typ. 244 |
[in] | diffthresh | thresh for the maximum difference between component values; below this the pixel is not considered to have sufficient color |
[in] | factor | subsampling factor |
[out] | ppixfract | fraction of pixels in intermediate brightness range that were considered for color content |
[out] | pcolorfract | fraction of pixels that meet the criterion for sufficient color; 0.0 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.
Definition at line 494 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
[in] | pixs | 32 bpp rgb or 8 bpp colormapped |
[in] | rref | reference value for red component |
[in] | gref | reference value for green component |
[in] | bref | reference value for blue component |
[in] | type | chooses the method for calculating the color magnitude: L_INTERMED_DIFF, L_AVE_MAX_DIFF_2, L_MAX_DIFF |
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.
Definition at line 362 of file colorcontent.c.
References CCBorda::h, L_AVE_MAX_DIFF_2, L_INTERMED_DIFF, L_MAX_DIFF, pixColorShiftWhitePoint(), pixCreate(), pixGetData(), pixGetDimensions(), and CCBorda::w.
l_ok pixColorsForQuantization | ( | PIX * | pixs, |
l_int32 | thresh, | ||
l_int32 * | pncolors, | ||
l_int32 * | piscolor, | ||
l_int32 | debug | ||
) |
[in] | pixs | 8 bpp gray or 32 bpp rgb; with or without colormap |
[in] | thresh | binary threshold on edge gradient; 0 for default |
[out] | pncolors | the number of colors found |
[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 |
[in] | debug | 1 to output masked image that is tested for colors; 0 otherwise |
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.
Definition at line 1286 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
[in] | pixs | 32 bpp rgb or 8 bpp colormapped |
[in] | rref | reference value for red component |
[in] | gref | reference value for green component |
[in] | bref | reference value for blue component |
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.
Definition at line 583 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
Referenced by pixColorContent(), and pixColorMagnitude().
[in] | pixs | 32 bpp RGB |
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.
Definition at line 1531 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
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 | ||
) |
[in] | pixs | 32 bpp rgb |
[in] | pixm | [optional] 1 bpp mask image |
[in] | factor | subsample factor; integer >= 1 |
[in] | lightthresh | threshold for component average in lightest of 10 buckets; typ. 210; -1 for default |
[in] | darkthresh | threshold to eliminate dark pixels (e.g., text) from consideration; typ. 70; -1 for default. |
[in] | mindiff | minimum difference (b - r) and (g - r), used to find blue or green pixels; typ. 10; -1 for default |
[in] | colordiff | minimum difference in (max - min) component to qualify as a color pixel; typ. 90; -1 for default |
[in] | edgefract | fraction of image half-width and half-height for which color pixels are ignored; typ. 0.05. |
[out] | pcolorfract | fraction of 'color' pixels found |
[out] | pcolormask1 | [optional] mask over background color, if any |
[out] | pcolormask2 | [optional] filtered mask over background color |
[out] | pixadb | [optional] debug intermediate results |
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.
Definition at line 947 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
l_ok pixGetMostPopulatedColors | ( | PIX * | pixs, |
l_int32 | sigbits, | ||
l_int32 | factor, | ||
l_int32 | ncolors, | ||
l_uint32 ** | parray, | ||
PIXCMAP ** | pcmap | ||
) |
[in] | pixs | 32 bpp rgb |
[in] | sigbits | 2-6, significant bits retained in the quantizer for each component of the input image |
[in] | factor | subsampling factor; use 1 for no subsampling |
[in] | ncolors | the number of most populated colors to select |
[out] | parray | [optional] array of colors, each as 0xrrggbb00 |
[out] | pcmap | [optional] colormap of the colors |
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, ...);
Definition at line 1628 of file colorcontent.c.
References CCBorda::n.
[in] | pixs | 32 bpp rgb |
[in] | sigbits | 2-6, significant bits retained in the quantizer for each component of the input image |
[in] | factor | subsampling factor; use 1 for no subsampling |
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().
Definition at line 1751 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
l_ok pixHasHighlightRed | ( | PIX * | pixs, |
l_int32 | factor, | ||
l_float32 | minfract, | ||
l_float32 | fthresh, | ||
l_int32 * | phasred, | ||
l_float32 * | pratio, | ||
PIX ** | ppixdb | ||
) |
[in] | pixs | 32 bpp rgb |
[in] | factor | subsampling; an integer >= 1; use 1 for all pixels |
[in] | minfract | threshold fraction of all image pixels; must be > 0.0 |
[in] | fthresh | threshold on a function of the components; typ. ~2.5 |
[out] | phasred | 1 if red pixels are above threshold |
[out] | pratio | [optional] normalized fraction of threshold red pixels that is actually observed |
[out] | ppixdb | [optional] seed pixel mask |
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.
Definition at line 1992 of file colorcontent.c.
[in] | pixs | 32 bpp rgb or 8 bpp colormapped |
[in] | threshdiff | threshold for minimum of the max difference between components |
[in] | mindist | min allowed distance from nearest non-color pixel |
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.
Definition at line 688 of file colorcontent.c.
References CCBorda::h, pixGetDimensions(), and CCBorda::w.
PIX* pixMaskOverColorRange | ( | PIX * | pixs, |
l_int32 | rmin, | ||
l_int32 | rmax, | ||
l_int32 | gmin, | ||
l_int32 | gmax, | ||
l_int32 | bmin, | ||
l_int32 | bmax | ||
) |
[in] | pixs | 32 bpp rgb or 8 bpp colormapped |
[in] | rmin,rmax | min and max allowed values for red component |
[in] | gmin,gmax | ditto for green |
[in] | bmin,bmax | ditto for blue |
Definition at line 828 of file colorcontent.c.
References CCBorda::h, pixGetDimensions(), and CCBorda::w.
[in] | pixs | 32 bpp rgb |
[in] | maxlimit | only consider pixels with max component <= maxlimit |
[in] | satlimit | only consider pixels with saturation <= satlimit |
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().
Definition at line 770 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
l_ok pixNumColors | ( | PIX * | pixs, |
l_int32 | factor, | ||
l_int32 * | pncolors | ||
) |
[in] | pixs | 2, 4, 8, 32 bpp |
[in] | factor | subsampling factor; integer |
[out] | pncolors | the number of colors found in the pix |
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.
Definition at line 1428 of file colorcontent.c.
References CCBorda::h, pixGetData(), pixGetDimensions(), and CCBorda::w.
l_ok pixNumSignificantGrayColors | ( | PIX * | pixs, |
l_int32 | darkthresh, | ||
l_int32 | lightthresh, | ||
l_float32 | minfract, | ||
l_int32 | factor, | ||
l_int32 * | pncolors | ||
) |
[in] | pixs | 8 bpp gray |
[in] | darkthresh | dark threshold for minimum intensity to be considered; typ. 20 |
[in] | lightthresh | threshold near white, for maximum intensity to be considered; typ. 236 |
[in] | minfract | minimum fraction of all pixels to include a level as significant; typ. 0.0001; should be < 0.001 |
[in] | factor | subsample factor; integer >= 1 |
[out] | pncolors | number of significant colors; 0 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.
Definition at line 1163 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.
[in] | pixs | 32 bpp rgb |
[in] | sigbits | 2-4, significant bits retained in the quantizer for each component of the input image |
[in] | factor | subsampling factor; use 1 for no subsampling |
[in] | ncolors | the number of most populated colors to select |
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.
Definition at line 1705 of file colorcontent.c.
References CCBorda::h, and CCBorda::w.