00001 /** \file
00002 * \brief Image Processing - Global Operations
00003 *
00004 * See Copyright Notice in im_lib.h
00005 */
00006
00007 #ifndef __IM_PROCESS_GLO_H
00008 #define __IM_PROCESS_GLO_H
00009
00010 #include "im_image.h"
00011
00012 #if defined(__cplusplus)
00013 extern "C" {
00014 #endif
00015
00016
00017
00018 /** \defgroup transform Other Domain Transform Operations
00019 * \par
00020 * Hough, Distance.
00021 *
00022 * See \ref im_process_glo.h
00023 * \ingroup process */
00024
00025 /** Hough Lines Transform. \n
00026 * It will detect white lines in a black background. So the source image must be a IM_BINARY image
00027 * with the white lines of interest enhanced. The better the threshold with the white lines the better
00028 * the line detection. \n
00029 * The destiny image must have IM_GRAY, IM_INT, hg_width=180, hg_height=2*rmax+1,
00030 * where rmax is the image diagonal/2 (rmax = srqrt(width*width + height*height)). \n
00031 * The hough transform defines "cos(theta) * X + sin(theta) * Y = rho" and the parameters are in the interval: \n
00032 * theta = "0 .. 179", rho = "-hg_height/2 .. hg_height/2" .\n
00033 * Where rho is the perpendicular distance from the center of the image and theta the angle with the normal.
00034 * So do not confuse theta with the line angle, they are perpendicular. \n
00035 * Returns zero if the counter aborted. \n
00036 * Inspired from ideas in XITE, Copyright 1991, Blab, UiO \n
00037 * http://www.ifi.uio.no/~blab/Software/Xite/
00038 *
00039 * \verbatim im.ProcessHoughLines(src_image: imImage, dst_image: imImage) -> counter: boolean [in Lua 5] \endverbatim
00040 * \verbatim im.ProcessHoughLinesNew(image: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim
00041 * \ingroup transform */
00042 int imProcessHoughLines(const imImage* src_image, imImage* dst_image);
00043
00044 /** Draw detected hough lines. \n
00045 * The source image must be IM_GRAY and IM_BYTE. The destiny image can be a clone of the source image or
00046 * it can be the source image for in place processing. \n
00047 * If the hough transform is not NULL, then the hough points are filtered to include only lines
00048 * that are significally different from each other. \n
00049 * The hough image is the hough transform image, but it is optional and can be NULL.
00050 * If not NULL then it will be used to filter lines that are very similar. \n
00051 * The hough points image is a hough transform image that was thresholded to a IM_BINARY image,
00052 * usually using a Local Max threshold operation (see \ref imProcessLocalMaxThreshold). Again the better the threshold the better the results. \n
00053 * The destiny image will be set to IM_MAP, and the detected lines will be drawn using a red color. \n
00054 * Returns the number of detected lines.
00055 *
00056 * \verbatim im.ProcessHoughLinesDraw(src_image: imImage, hough: imImage, hough_points: imImage, dst_image: imImage) -> lines: number [in Lua 5] \endverbatim
00057 * \verbatim im.ProcessHoughLinesDrawNew(image: imImage, hough: imImage, hough_points: imImage) -> lines: number, new_image: imImage [in Lua 5] \endverbatim
00058 * \ingroup transform */
00059 int imProcessHoughLinesDraw(const imImage* src_image, const imImage* hough, const imImage* hough_points, imImage* dst_image);
00060
00061 /** Calculates the Cross Correlation in the frequency domain. \n
00062 * CrossCorr(a,b) = IFFT(Conj(FFT(a))*FFT(b)) \n
00063 * Images must be of the same size and only destiny image must be of type complex.
00064 *
00065 * \verbatim im.ProcessCrossCorrelation(src_image1: imImage, src_image2: imImage, dst_image: imImage) [in Lua 5] \endverbatim
00066 * \verbatim im.ProcessCrossCorrelationNew(image1: imImage, image2: imImage) -> new_image: imImage [in Lua 5] \endverbatim
00067 * \ingroup transform */
00068 void imProcessCrossCorrelation(const imImage* src_image1, const imImage* src_image2, imImage* dst_image);
00069
00070 /** Calculates the Auto Correlation in the frequency domain. \n
00071 * Uses the cross correlation.
00072 * Images must be of the same size and only destiny image must be of type complex.
00073 *
00074 * \verbatim im.ProcessAutoCorrelation(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
00075 * \verbatim im.ProcessAutoCorrelationNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
00076 * \ingroup transform */
00077 void imProcessAutoCorrelation(const imImage* src_image, imImage* dst_image);
00078
00079 /** Calculates the Distance Transform of a binary image
00080 * using an aproximation of the euclidian distance.\n
00081 * Each white pixel in the binary image is
00082 * assigned a value equal to its distance from the nearest
00083 * black pixel. \n
00084 * Uses a two-pass algorithm incrementally calculating the distance. \n
00085 * Source image must be IM_BINARY, destiny must be IM_FLOAT.
00086 *
00087 * \verbatim im.ProcessDistanceTransform(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
00088 * \verbatim im.ProcessDistanceTransformNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
00089 * \ingroup transform */
00090 void imProcessDistanceTransform(const imImage* src_image, imImage* dst_image);
00091
00092 /** Marks all the regional maximum of the distance transform. \n
00093 * source is IMGRAY/IM_FLOAT destiny in IM_BINARY. \n
00094 * We consider maximum all connected pixel values that have smaller pixel values around it.
00095 *
00096 * \verbatim im.ProcessRegionalMaximum(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
00097 * \verbatim im.ProcessRegionalMaximumNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
00098 * \ingroup transform */
00099 void imProcessRegionalMaximum(const imImage* src_image, imImage* dst_image);
00100
00101
00102
00103 /** \defgroup fourier Fourier Transform Operations
00104 * \par
00105 * All Fourier transforms use FFTW library version 2.1.5. \n
00106 * Although there are newer versions, we build binaries only to version 2
00107 * because it is small and as fast as newer versions.
00108 * Source code to use FFTW version 3 is available.
00109 * \par
00110 * FFTW Copyright Matteo Frigo, Steven G. Johnson and the MIT. \n
00111 * http://www.fftw.org \n
00112 * See "fftw.h"
00113 * \par
00114 * Must link with "im_fftw" library. \n
00115 * \par
00116 * The FFTW lib has a GPL license. The license of the "im_fftw" library is automatically the GPL.
00117 * So you cannot use it for commercial applications without contacting the authors.
00118 * \par
00119 * See \ref im_process_glo.h
00120 * \ingroup process */
00121
00122 /** Forward FFT. \n
00123 * The result has its lowest frequency at the center of the image. \n
00124 * This is an unnormalized fft. \n
00125 * Images must be of the same size. Destiny image must be of type complex.
00126 *
00127 * \verbatim im.ProcessFFT(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
00128 * \verbatim im.ProcessFFTNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
00129 * \ingroup fourier */
00130 void imProcessFFT(const imImage* src_image, imImage* dst_image);
00131
00132 /** Inverse FFT. \n
00133 * The image has its lowest frequency restored to the origin before the transform. \n
00134 * The result is normalized by (width*height). \n
00135 * Images must be of the same size and both must be of type complex.
00136 *
00137 * \verbatim im.ProcessIFFT(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
00138 * \verbatim im.ProcessIFFTNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
00139 * \ingroup fourier */
00140 void imProcessIFFT(const imImage* src_image, imImage* dst_image);
00141
00142 /** Raw in-place FFT (forward or inverse). \n
00143 * The lowest frequency can be centered after forward, or
00144 * can be restored to the origin before inverse. \n
00145 * The result can be normalized after the transform by sqrt(w*h) [1] or by (w*h) [2],
00146 * or left unnormalized [0]. \n
00147 * Images must be of the same size and both must be of type complex.
00148 *
00149 * \verbatim im.ProcessFFTraw(image: imImage, inverse: number, center: number, normalize: number) [in Lua 5] \endverbatim
00150 * \ingroup fourier */
00151 void imProcessFFTraw(imImage* image, int inverse, int center, int normalize);
00152
00153 /** Auxiliary function for the raw FFT. \n
00154 * This is the function used internally to change the lowest frequency position in the image. \n
00155 * If the image size has even dimensions the flag "center2origin" is useless. But if it is odd,
00156 * you must specify if its from center to origin (usually used before inverse) or
00157 * from origin to center (usually used after forward). \n
00158 * Notice that this function is used for images in the the frequency domain. \n
00159 * Image type must be complex.
00160 *
00161 * \verbatim im.ProcessSwapQuadrants(image: imImage, center2origin: number) [in Lua 5] \endverbatim
00162 * \ingroup fourier */
00163 void imProcessSwapQuadrants(imImage* image, int center2origin);
00164
00165
00166 #if defined(__cplusplus)
00167 }
00168 #endif
00169
00170 #endif