Initial import. Contains the im, cd and iup librairies, and a "working" Makefile for them under linux.

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+/** \file
+ * \brief Image Processing - Global Operations
+ *
+ * See Copyright Notice in im_lib.h
+ */
+
+#ifndef __IM_PROCESS_GLO_H
+#define __IM_PROCESS_GLO_H
+
+#include "im_image.h"
+
+#if	defined(__cplusplus)
+extern "C" {
+#endif
+
+
+
+/** \defgroup transform Other Domain Transform Operations
+ * \par
+ * Hough, Distance.
+ *
+ * See \ref im_process_glo.h
+ * \ingroup process */
+
+/** Hough Lines Transform. \n
+ * It will detect white lines in a black background. So the source image must be a IM_BINARY image 
+ * with the white lines of interest enhanced. The better the threshold with the white lines the better 
+ * the line detection. \n
+ * The destiny image must have IM_GRAY, IM_INT, hg_width=180, hg_height=2*rmax+1, 
+ * where rmax is the image diagonal/2 (rmax = srqrt(width*width + height*height)). \n
+ * The hough transform defines  "cos(theta) * X  + sin(theta) * Y = rho" and the parameters are in the interval: \n
+ * theta = "0 .. 179", rho = "-hg_height/2 .. hg_height/2" .\n
+ * Where rho is the perpendicular distance from the center of the image and theta the angle with the normal.
+ * So do not confuse theta with the line angle, they are perpendicular. \n
+ * Returns zero if the counter aborted. \n
+ * Inspired from ideas in XITE, Copyright 1991, Blab, UiO \n
+ * http://www.ifi.uio.no/~blab/Software/Xite/
+ *
+ * \verbatim im.ProcessHoughLines(src_image: imImage, dst_image: imImage) -> counter: boolean [in Lua 5] \endverbatim
+ * \verbatim im.ProcessHoughLinesNew(image: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup transform */
+int imProcessHoughLines(const imImage* src_image, imImage* dst_image);
+
+/** Draw detected hough lines. \n
+ * The source image must be IM_GRAY and IM_BYTE. The destiny image can be a clone of the source image or 
+ * it can be the source image for in place processing. \n
+ * If the hough transform is not NULL, then the hough points are filtered to include only lines
+ * that are significally different from each other. \n
+ * The hough image is the hough transform image, but it is optional and can be NULL. 
+ * If not NULL then it will be used to filter lines that are very similar. \n
+ * The hough points image is a hough transform image that was thresholded to a IM_BINARY image, 
+ * usually using a Local Max threshold operation (see \ref imProcessLocalMaxThreshold). Again the better the threshold the better the results. \n
+ * The destiny image will be set to IM_MAP, and the detected lines will be drawn using a red color. \n
+ * Returns the number of detected lines.
+ *
+ * \verbatim im.ProcessHoughLinesDraw(src_image: imImage, hough: imImage, hough_points: imImage, dst_image: imImage) -> lines: number [in Lua 5] \endverbatim
+ * \verbatim im.ProcessHoughLinesDrawNew(image: imImage, hough: imImage, hough_points: imImage) -> lines: number, new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup transform */
+int imProcessHoughLinesDraw(const imImage* src_image, const imImage* hough, const imImage* hough_points, imImage* dst_image);
+
+/** Calculates the Cross Correlation in the frequency domain. \n 
+ * CrossCorr(a,b) = IFFT(Conj(FFT(a))*FFT(b)) \n
+ * Images must be of the same size and only destiny image must be of type complex.
+ *
+ * \verbatim im.ProcessCrossCorrelation(src_image1: imImage, src_image2: imImage, dst_image: imImage) [in Lua 5] \endverbatim
+ * \verbatim im.ProcessCrossCorrelationNew(image1: imImage, image2: imImage) -> new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup transform */
+void imProcessCrossCorrelation(const imImage* src_image1, const imImage* src_image2, imImage* dst_image);
+
+/** Calculates the Auto Correlation in the frequency domain. \n 
+ * Uses the cross correlation.
+ * Images must be of the same size and only destiny image must be of type complex.
+ *
+ * \verbatim im.ProcessAutoCorrelation(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
+ * \verbatim im.ProcessAutoCorrelationNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup transform */
+void imProcessAutoCorrelation(const imImage* src_image, imImage* dst_image);
+
+/** Calculates the Distance Transform of a binary image 
+ * using an aproximation of the euclidian distance.\n
+ * Each white pixel in the binary image is
+ * assigned a value equal to its distance from the nearest
+ * black pixel. \n
+ * Uses a two-pass algorithm incrementally calculating the distance. \n
+ * Source image must be IM_BINARY, destiny must be IM_FLOAT.
+ *
+ * \verbatim im.ProcessDistanceTransform(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
+ * \verbatim im.ProcessDistanceTransformNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup transform */
+void imProcessDistanceTransform(const imImage* src_image, imImage* dst_image);
+
+/** Marks all the regional maximum of the distance transform. \n
+ * source is IMGRAY/IM_FLOAT destiny in IM_BINARY. \n
+ * We consider maximum all connected pixel values that have smaller pixel values around it.
+ *
+ * \verbatim im.ProcessRegionalMaximum(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
+ * \verbatim im.ProcessRegionalMaximumNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup transform */
+void imProcessRegionalMaximum(const imImage* src_image, imImage* dst_image);
+
+
+
+/** \defgroup fourier Fourier Transform Operations
+ * \par
+ * All Fourier transforms use FFTW library. \n
+ * The pre-compiled binaries for FFTW version 2.1.5 includes all the necessary files.
+ * The pre-compiled binaries for FFTW version 3.x depends on an external library, not provided.
+ * To build the code that uses FFTW version 3 you must define USE_FFTW3.
+ * \par
+ * FFTW Copyright Matteo Frigo, Steven G. Johnson and the MIT. \n
+ * http://www.fftw.org                                         \n
+ * See "fftw.h"
+ * \par
+ * Must link with "im_fftw" library. \n
+ * \par
+ * IMPORTANT: The FFTW lib has a GPL license. The license of the "im_fftw" library is automatically the GPL.
+ * So you cannot use it for commercial applications without contacting the authors. 
+ * \par
+ * See \ref im_process_glo.h
+ * \ingroup process */
+
+/** Forward FFT. \n
+ * The result has its lowest frequency at the center of the image. \n
+ * This is an unnormalized fft. \n
+ * Images must be of the same size. Destiny image must be of type complex.
+ *
+ * \verbatim im.ProcessFFT(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
+ * \verbatim im.ProcessFFTNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup fourier */
+void imProcessFFT(const imImage* src_image, imImage* dst_image);
+
+/** Inverse FFT. \n
+ * The image has its lowest frequency restored to the origin before the transform. \n
+ * The result is normalized by (width*height). \n
+ * Images must be of the same size and both must be of type complex.
+ *
+ * \verbatim im.ProcessIFFT(src_image: imImage, dst_image: imImage) [in Lua 5] \endverbatim
+ * \verbatim im.ProcessIFFTNew(image: imImage) -> new_image: imImage [in Lua 5] \endverbatim
+ * \ingroup fourier */
+void imProcessIFFT(const imImage* src_image, imImage* dst_image);
+
+/** Raw in-place FFT (forward or inverse). \n
+ * The lowest frequency can be centered after forward, or
+ * can be restored to the origin before inverse. \n
+ * The result can be normalized after the transform by sqrt(w*h) [1] or by (w*h) [2], 
+ * or left unnormalized [0]. \n
+ * Images must be of the same size and both must be of type complex.
+ *
+ * \verbatim im.ProcessFFTraw(image: imImage, inverse: number, center: number, normalize: number) [in Lua 5] \endverbatim
+ * \ingroup fourier */
+void imProcessFFTraw(imImage* image, int inverse, int center, int normalize);
+
+/** Auxiliary function for the raw FFT. \n 
+ * This is the function used internally to change the lowest frequency position in the image. \n
+ * If the image size has even dimensions the flag "center2origin" is useless. But if it is odd, 
+ * you must specify if its from center to origin (usually used before inverse) or
+ * from origin to center (usually used after forward). \n
+ * Notice that this function is used for images in the the frequency domain. \n
+ * Image type must be complex.
+ *
+ * \verbatim im.ProcessSwapQuadrants(image: imImage, center2origin: number) [in Lua 5] \endverbatim
+ * \ingroup fourier */
+void imProcessSwapQuadrants(imImage* image, int center2origin);
+
+
+#if defined(__cplusplus)
+}
+#endif
+
+#endif