/** \file * \brief Image Statistics and Analysis * * See Copyright Notice in im_lib.h */ #ifndef __IM_PROC_ANA_H #define __IM_PROC_ANA_H #include "im_image.h" #if defined(__cplusplus) extern "C" { #endif /** \defgroup stats Image Statistics Calculations * \par * Operations to calculate some statistics over images. * \par * See \ref im_process_ana.h * \ingroup process */ /** Calculates the RMS error between two images (Root Mean Square Error). * * \verbatim im.CalcRMSError(image1: imImage, image2: imImage) -> rms: number [in Lua 5] \endverbatim * \ingroup stats */ float imCalcRMSError(const imImage* image1, const imImage* image2); /** Calculates the SNR of an image and its noise (Signal Noise Ratio). * * \verbatim im.CalcSNR(src_image: imImage, noise_image: imImage) -> snr: number [in Lua 5] \endverbatim * \ingroup stats */ float imCalcSNR(const imImage* src_image, const imImage* noise_image); /** Count the number of different colors in an image. \n * Image must be IM_BYTE, but all color spaces except IM_CMYK. * * \verbatim im.CalcCountColors(image: imImage) -> count: number [in Lua 5] \endverbatim * \ingroup stats */ unsigned long imCalcCountColors(const imImage* image); /** Calculates the histogram of a IM_BYTE data. \n * Histogram is always 256 positions long. \n * When cumulative is different from zero it calculates the cumulative histogram. * * \verbatim im.CalcHistogram(image: imImage, plane: number, cumulative: boolean) -> histo: table of numbers [in Lua 5] \endverbatim * Where plane is the depth plane to calculate the histogram. \n * The returned table is zero indexed. image can be IM_USHORT or IM_BYTE. * \ingroup stats */ void imCalcHistogram(const unsigned char* data, int count, unsigned long* histo, int cumulative); /** Calculates the histogram of a IM_USHORT data. \n * Histogram is always 65535 positions long. \n * When cumulative is different from zero it calculates the cumulative histogram. \n * Use \ref imCalcHistogram in Lua. * \ingroup stats */ void imCalcUShortHistogram(const unsigned short* data, int count, unsigned long* histo, int cumulative); /** Calculates the gray histogram of an image. \n * Image must be IM_BYTE/(IM_RGB, IM_GRAY, IM_BINARY or IM_MAP). \n * If the image is IM_RGB then the histogram of the luma component is calculated. \n * Histogram is always 256 positions long. \n * When cumulative is different from zero it calculates the cumulative histogram. * * \verbatim im.CalcGrayHistogram(image: imImage, cumulative: boolean) -> histo: table of numbers [in Lua 5] \endverbatim * \ingroup stats */ void imCalcGrayHistogram(const imImage* image, unsigned long* histo, int cumulative); /** Numerical Statistics Structure * \ingroup stats */ typedef struct _imStats { float max; /**< Maximum value */ float min; /**< Minimum value */ unsigned long positive; /**< Number of Positive Values */ unsigned long negative; /**< Number of Negative Values */ unsigned long zeros; /**< Number of Zeros */ float mean; /**< Mean */ float stddev; /**< Standard Deviation */ } imStats; /** Calculates the statistics about the image data. \n * There is one stats for each depth plane. For ex: stats[0]=red stats, stats[0]=green stats, ... \n * Supports all data types except IM_CFLOAT. \n * * \verbatim im.CalcImageStatistics(image: imImage) -> stats: table [in Lua 5] \endverbatim * Table contains the following fields: max, min, positive, negative, zeros, mean, stddev. * The same as the \ref imStats structure. * \ingroup stats */ void imCalcImageStatistics(const imImage* image, imStats* stats); /** Calculates the statistics about the image histogram data.\n * There is one stats for each depth plane. For ex: stats[0]=red stats, stats[0]=green stats, ... \n * Only IM_BYTE images are supported. * * \verbatim im.CalcHistogramStatistics(image: imImage) -> stats: table [in Lua 5] \endverbatim * \ingroup stats */ void imCalcHistogramStatistics(const imImage* image, imStats* stats); /** Calculates some extra statistics about the image histogram data.\n * There is one stats for each depth plane. \n * Only IM_BYTE images are supported. \n * mode will be -1 if more than one max is found. * * \verbatim im.CalcHistoImageStatistics(image: imImage) -> median: number, mode: number [in Lua 5] \endverbatim * \ingroup stats */ void imCalcHistoImageStatistics(const imImage* image, int* median, int* mode); /** \defgroup analyze Image Analysis * \par * See \ref im_process_ana.h * \ingroup process */ /** Find white regions in binary image. \n * Result is IM_GRAY/IM_USHORT type. Regions can be 4 connected or 8 connected. \n * Returns the number of regions found. Background is marked as 0. \n * Regions touching the border are considered only if touch_border=1. * * \verbatim im.AnalyzeFindRegions(src_image: imImage, dst_image: imImage, connect: number, touch_border: boolean) -> count: number [in Lua 5] \endverbatim * \verbatim im.AnalyzeFindRegionsNew(image: imImage, connect: number, touch_border: boolean) -> count: number, new_image: imImage [in Lua 5] \endverbatim * \ingroup analyze */ int imAnalyzeFindRegions(const imImage* src_image, imImage* dst_image, int connect, int touch_border); /** Measure the actual area of all regions. Holes are not included. \n * This is the number of pixels of each region. \n * Source image is IM_GRAY/IM_USHORT type (the result of \ref imAnalyzeFindRegions). \n * area has size the number of regions. * * \verbatim im.AnalyzeMeasureArea(image: imImage, [region_count: number]) -> area: table of numbers [in Lua 5] \endverbatim * The returned table is zero indexed. * \ingroup analyze */ void imAnalyzeMeasureArea(const imImage* image, int* area, int region_count); /** Measure the polygonal area limited by the perimeter line of all regions. Holes are not included. \n * Notice that some regions may have polygonal area zero. \n * Source image is IM_GRAY/IM_USHORT type (the result of \ref imAnalyzeFindRegions). \n * perimarea has size the number of regions. * * \verbatim im.AnalyzeMeasurePerimArea(image: imImage, [region_count: number]) -> perimarea: table of numbers [in Lua 5] \endverbatim * The returned table is zero indexed. * \ingroup analyze */ void imAnalyzeMeasurePerimArea(const imImage* image, float* perimarea); /** Calculate the centroid position of all regions. Holes are not included. \n * Source image is IM_GRAY/IM_USHORT type (the result of \ref imAnalyzeFindRegions). \n * area, cx and cy have size the number of regions. If area is NULL will be internally calculated. * * \verbatim im.AnalyzeMeasureCentroid(image: imImage, [area: table of numbers], [region_count: number]) -> cx: table of numbers, cy: table of numbers [in Lua 5] \endverbatim * The returned tables are zero indexed. * \ingroup analyze */ void imAnalyzeMeasureCentroid(const imImage* image, const int* area, int region_count, float* cx, float* cy); /** Calculate the principal major axis slope of all regions. \n * Source image is IM_GRAY/IM_USHORT type (the result of \ref imAnalyzeFindRegions). \n * data has size the number of regions. If area or centroid are NULL will be internally calculated. \n * Principal (major and minor) axes are defined to be those axes that pass through the * centroid, about which the moment of inertia of the region is, respectively maximal or minimal. * * \verbatim im.AnalyzeMeasurePrincipalAxis(image: imImage, [area: table of numbers], [cx: table of numbers], [cy: table of numbers], [region_count: number]) -> major_slope: table of numbers, major_length: table of numbers, minor_slope: table of numbers, minor_length: table of numbers [in Lua 5] \endverbatim * The returned tables are zero indexed. * \ingroup analyze */ void imAnalyzeMeasurePrincipalAxis(const imImage* image, const int* area, const float* cx, const float* cy, const int region_count, float* major_slope, float* major_length, float* minor_slope, float* minor_length); /** Measure the number and area of holes of all regions. \n * Source image is IM_USHORT type (the result of \ref imAnalyzeFindRegions). \n * area and perim has size the number of regions, if some is NULL it will be not calculated. * * \verbatim im.AnalyzeMeasureHoles(image: imImage, connect: number, [region_count: number]) -> holes_count: number, area: table of numbers, perim: table of numbers [in Lua 5] \endverbatim * The returned tables are zero indexed. * \ingroup analyze */ void imAnalyzeMeasureHoles(const imImage* image, int connect, int *holes_count, int* area, float* perim); /** Measure the total perimeter of all regions (external and internal). \n * Source image is IM_GRAY/IM_USHORT type (the result of imAnalyzeFindRegions). \n * It uses a half-pixel inter distance for 8 neighboors in a perimeter of a 4 connected region. \n * This function can also be used to measure line lenght. \n * perim has size the number of regions. * * \verbatim im.AnalyzeMeasurePerimeter(image: imImage) -> perim: table of numbers [in Lua 5] \endverbatim * \ingroup analyze */ void imAnalyzeMeasurePerimeter(const imImage* image, float* perim, int region_count); /** Isolates the perimeter line of gray integer images. Background is defined as being black (0). \n * It just checks if at least one of the 4 connected neighboors is non zero. Image borders are extended with zeros. * * \verbatim im.ProcessPerimeterLine(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim * \verbatim im.ProcessPerimeterLineNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup analyze */ void imProcessPerimeterLine(const imImage* src_image, imImage* dst_image); /** Eliminates regions that have size outside the given interval. \n * Source and destiny are a binary images. Regions can be 4 connected or 8 connected. \n * Can be done in-place. end_size can be zero to ignore big objects. * * \verbatim im.ProcessPrune(src_image: imImage, dst_image: imImage, connect: number, start_size: number, end_size: number) [in Lua 5] \endverbatim * \verbatim im.ProcessPruneNew(image: imImage, connect: number, start_size: number, end_size: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup analyze */ void imProcessPrune(const imImage* src_image, imImage* dst_image, int connect, int start_size, int end_size); /** Fill holes inside white regions. \n * Source and destiny are a binary images. Regions can be 4 connected or 8 connected. \n * Can be done in-place. * * \verbatim im.ProcessFillHoles(src_image: imImage, dst_image: imImage, connect: number) [in Lua 5] \endverbatim * \verbatim im.ProcessFillHolesNew(image: imImage, connect: number) -> new_image: imImage [in Lua 5] \endverbatim * \ingroup analyze */ void imProcessFillHoles(const imImage* src_image, imImage* dst_image, int connect); #if defined(__cplusplus) } #endif #endif