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/** \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
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