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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: number) -> 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: number) -> 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: number) -> count: number [in Lua 5] \endverbatim
+ * \verbatim im.AnalyzeFindRegionsNew(image: imImage, connect: number, touch_border: number) -> 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