430 lines
14 KiB
C
430 lines
14 KiB
C
/*
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* =====================================================================================
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*
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* Filename: libcvautomation-opencv.c
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*
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* Description:
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*
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* Created: 06/21/2012 08:34:21 AM
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* Revision: none
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* Compiler: gcc
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*
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* Author: Bradlee Speice, bspeice@uncc.edu
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* Organization: MOSAIC at University of North Carolina at Charlotte
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*
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* =====================================================================================
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*/
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#include <libcvautomation/libcvautomation-opencv.h>
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage
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* Returns: CvPoint if a match is found, null if not
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* =====================================================================================
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*/
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cvaPoint matchSubImage ( IplImage *rootImage, IplImage *subImage, int searchMethod, double tolerance )
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{
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/* We have the two OpenCV images we want, go ahead and find if there are any matches */
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IplImage *result;
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CvPoint minloc, maxloc; /* Location for the match - depending on search algorithm,
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the result may be in either minloc or maxloc */
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cvaPoint returnPoint; /* (-1, -1), used to indicate an error */
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double minval, maxval;
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int rootImage_width, rootImage_height;
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int subImage_width, subImage_height;
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int result_width, result_height;
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returnPoint.x = returnPoint.y = -1;
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/* Make sure we have valid images */
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if ( rootImage == 0 || subImage == 0) {
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/* Otherwise return invalid */
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return returnPoint;
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}
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/* Set up the parameters for our result image */
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rootImage_width = rootImage->width;
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rootImage_height = rootImage->height;
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subImage_width = subImage->width;
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subImage_height = subImage->height;
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result_width = rootImage_width - subImage_width + 1;
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result_height = rootImage_height - subImage_height + 1;
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/* Initialize our result image */
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result = cvCreateImage( cvSize( result_width, result_height ), IPL_DEPTH_32F, 1 );
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/* Compute the result image */
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cvMatchTemplate( rootImage, subImage, result, searchMethod );
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cvMinMaxLoc( result, &minval, &maxval, &minloc, &maxloc, 0 );
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/* Free memory for the result image
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* Note that we don't control the root or sub image,
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* so don't mess with those */
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cvReleaseImage( &result );
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/* Make sure that we have enough correlation to return a result,
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* and then return the match location*/
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/* Return the match location */
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if ( searchMethod == CV_TM_SQDIFF || searchMethod == CV_TM_SQDIFF_NORMED )
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{
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if ( minval < tolerance )
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{
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returnPoint.x = minloc.x;
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returnPoint.y = minloc.y;
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return returnPoint;
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}
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else
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/* Return invalid */
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return returnPoint;
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}
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else
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{
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if ( maxval > tolerance )
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{
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returnPoint.x = maxloc.x;
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returnPoint.y = maxloc.y;
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return returnPoint;
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}
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else
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/* Return invalid */
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return returnPoint;
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}
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} /* ----- end of function matchSubImage ----- */
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_location
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* Description: Match a root image and sub image from filename
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* =====================================================================================
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*/
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cvaPoint matchSubImage_location ( const char *rootImage_location, const char *subImage_location, int searchMethod, double tolerance )
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{
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/* This is basically a wrapper for matchSubImage( IplImage, IplImage )
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* All we do is load the images from the given filenames, and then
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* pass off the result to the above-named function */
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IplImage *rootImage;
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rootImage = cvLoadImage( rootImage_location, CV_LOAD_IMAGE_COLOR );
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IplImage *subImage;
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subImage = cvLoadImage( subImage_location, CV_LOAD_IMAGE_COLOR );
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cvaPoint resultPoint;
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resultPoint.x = resultPoint.y = -1;
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/* Make sure we have good images */
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if ( rootImage == 0 || subImage == 0 )
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{
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/* Return error */
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return resultPoint;
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}
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resultPoint = matchSubImage( rootImage, subImage, searchMethod, tolerance );
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/* Free up the memory we created */
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cvReleaseImage( &rootImage );
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cvReleaseImage( &subImage );
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/* Our resultPoint will already be invalid if there's no match */
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return resultPoint;
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} /* ----- end of function matchSubImage ----- */
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_a
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* Description: Match a root image and sub image from an array of sub-images.
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* The list contains an element for each sub-image to specify its own
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* searchMethod and threshold value.
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* =====================================================================================
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*/
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void matchSubImage_a ( IplImage *rootImage, cvautomationList *subImageArray, int listSize )
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{
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/* This is also a higher-end wrapper for matchSubImage, but is mostly aimed
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* at making python support for multiple images very easy. */
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cvaPoint resultPoint;
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cvautomationList curr;
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int x = 0;
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for ( x = 0; x < listSize; x++ )
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{
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curr = subImageArray[x];
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if ( subImageArray[x].cvaImage != 0 )
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resultPoint = matchSubImage ( rootImage, curr.cvaImage, curr.searchMethod, curr.tolerance );
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else
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{
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/* We have a sub-image filename, go ahead and create the actual image. */
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IplImage *subImage;
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subImage = cvLoadImage( curr.fileName, CV_LOAD_IMAGE_COLOR );
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resultPoint = matchSubImage ( rootImage, subImage, curr.searchMethod, curr.tolerance );
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cvReleaseImage( &subImage );
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}
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curr.resultPoint = resultPoint;
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}
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}
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_a_location
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* Description: Match a root image from location, and sub image from
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* an array of sub-images.
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* The list contains an element for each sub-image to specify its own
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* searchMethod and threshold value.
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* =====================================================================================
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*/
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void matchSubImage_a_location ( const char *rootImage_location, cvautomationList *subImageArray, int listSize )
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{
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/* This is also a higher-end wrapper for matchSubImage, but is mostly aimed
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* at making python support for multiple images very easy. */
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cvaPoint resultPoint;
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cvautomationList curr;
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IplImage *rootImage;
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rootImage = cvLoadImage( rootImage_location, CV_LOAD_IMAGE_COLOR );
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int x = 0;
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for ( x = 0; x < listSize; x++ )
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{
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curr = subImageArray[x];
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if ( subImageArray[x].cvaImage != 0 )
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resultPoint = matchSubImage ( rootImage, curr.cvaImage, curr.searchMethod, curr.tolerance );
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else
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{
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/* We have a sub-image filename, go ahead and create the actual image. */
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IplImage *subImage;
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subImage = cvLoadImage( curr.fileName, CV_LOAD_IMAGE_COLOR );
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resultPoint = matchSubImage ( rootImage, subImage, curr.searchMethod, curr.tolerance );
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cvReleaseImage( &subImage );
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}
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curr.resultPoint = resultPoint;
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}
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cvReleaseImage( &rootImage );
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}
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_center
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* Returns: CvPoint if a match is found, null if not
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* The code is mostly the same as matchSubImage, but the difference
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* here is that it returns the center of the sub-image, rather than
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* the top-left corner.
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* =====================================================================================
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*/
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cvaPoint matchSubImage_center ( IplImage *rootImage, IplImage *subImage, int searchMethod, double tolerance )
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{
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/* We have the two OpenCV images we want, go ahead and find if there are any matches */
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IplImage *result;
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CvPoint minloc, maxloc; /* Location for the match - depending on search algorithm,
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the result may be in either minloc or maxloc */
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cvaPoint returnPoint; /* (-1, -1), used to indicate an error */
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double minval, maxval;
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int rootImage_width, rootImage_height;
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int subImage_width, subImage_height;
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int result_width, result_height;
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returnPoint.x = returnPoint.y = -1;
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/* Make sure we have valid images */
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if ( rootImage == 0 || subImage == 0) {
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/* Otherwise return invalid */
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return returnPoint;
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}
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/* Set up the parameters for our result image */
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rootImage_width = rootImage->width;
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rootImage_height = rootImage->height;
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subImage_width = subImage->width;
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subImage_height = subImage->height;
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result_width = rootImage_width - subImage_width + 1;
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result_height = rootImage_height - subImage_height + 1;
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/* Initialize our result image */
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result = cvCreateImage( cvSize( result_width, result_height ), IPL_DEPTH_32F, 1 );
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/* Compute the result image */
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cvMatchTemplate( rootImage, subImage, result, searchMethod );
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cvMinMaxLoc( result, &minval, &maxval, &minloc, &maxloc, 0 );
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/* Free memory for the result image
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* Note that we don't control the root or sub image,
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* so don't mess with those */
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cvReleaseImage( &result );
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/* Make sure that we have enough correlation to return a result,
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* and then return the match location*/
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/* Return the match location */
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if ( searchMethod == CV_TM_SQDIFF || searchMethod == CV_TM_SQDIFF_NORMED )
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{
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if ( minval < tolerance )
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{
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returnPoint.x = minloc.x;
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returnPoint.y = minloc.y;
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/* Center the image before returning */
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returnPoint.x += (subImage->width) / 2;
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returnPoint.y += (subImage->height) / 2;
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return returnPoint;
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}
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else
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/* Return invalid */
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return returnPoint;
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}
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else
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{
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if ( maxval > tolerance )
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{
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returnPoint.x = maxloc.x;
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returnPoint.y = maxloc.y;
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/* Center the image before returning */
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returnPoint.x += (subImage->width) / 2;
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returnPoint.y += (subImage->height) / 2;
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return returnPoint;
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}
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else
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/* Return invalid */
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return returnPoint;
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}
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} /* ----- end of function matchSubImage_center ----- */
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_location_center
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* Description: Match a root image and sub image from filename
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* Most of the code is the same as matchSubImage_location, but use
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* matchSubImage_center as the lower-level call to make sure that
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* we get the center of the sub-image.
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* =====================================================================================
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*/
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cvaPoint matchSubImage_location_center ( const char *rootImage_location, const char *subImage_location, int searchMethod, double tolerance )
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{
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/* This is basically a wrapper for matchSubImage( IplImage, IplImage )
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* All we do is load the images from the given filenames, and then
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* pass off the result to the above-named function */
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IplImage *rootImage;
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rootImage = cvLoadImage( rootImage_location, CV_LOAD_IMAGE_COLOR );
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IplImage *subImage;
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subImage = cvLoadImage( subImage_location, CV_LOAD_IMAGE_COLOR );
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cvaPoint resultPoint;
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resultPoint.x = resultPoint.y = -1;
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/* Make sure we have good images */
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if ( rootImage == 0 || subImage == 0 )
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{
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/* Return error */
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return resultPoint;
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}
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resultPoint = matchSubImage_center( rootImage, subImage, searchMethod, tolerance );
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/* Free up the memory we created */
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cvReleaseImage( &rootImage );
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cvReleaseImage( &subImage );
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/* Our return_point will already be NULL if there's no match */
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return resultPoint;
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} /* ----- end of function matchSubImage_location_center ----- */
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_a_center
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* Description: Match a root image and sub image from an array of sub-images.
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* The list contains an element for each sub-image to specify its own
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* searchMethod and threshold value.
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* Most of the code is the same as matchSubImage_a, but we use
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* matchSubImage_center as the underlying function to make sure we
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* get the center of the sub-image, rather than the top-left corner
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* =====================================================================================
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*/
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void matchSubImage_a_center ( IplImage *rootImage, cvautomationList *subImageArray, int listSize )
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{
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/* This is also a higher-end wrapper for matchSubImage, but is mostly aimed
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* at making python support for multiple images very easy. */
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cvaPoint resultPoint;
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cvautomationList curr;
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int x = 0;
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for ( x = 0; x < listSize; x++ )
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{
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curr = subImageArray[x];
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if ( subImageArray[x].cvaImage != 0 )
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resultPoint = matchSubImage ( rootImage, curr.cvaImage, curr.searchMethod, curr.tolerance );
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else
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{
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/* We have a sub-image filename, go ahead and create the actual image. */
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IplImage *subImage;
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subImage = cvLoadImage( curr.fileName, CV_LOAD_IMAGE_COLOR );
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resultPoint = matchSubImage_center ( rootImage, subImage, curr.searchMethod, curr.tolerance );
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cvReleaseImage( &subImage );
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}
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curr.resultPoint = resultPoint;
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}
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}
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/*
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* === FUNCTION ======================================================================
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* Name: matchSubImage_a_location_center
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* Description: Match a root image from location, and sub image from
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* an array of sub-images.
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* The list contains an element for each sub-image to specify its own
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* searchMethod and threshold value.
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* Most of the code is the same as matchSubImage_a_location, but we
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* use matchSubImage_center in order to return the center of the sub-
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* image, rather than the top-left corner.
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* =====================================================================================
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*/
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void matchSubImage_a_location_center ( const char *rootImage_location, cvautomationList *subImageArray, int listSize )
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{
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/* This is also a higher-end wrapper for matchSubImage, but is mostly aimed
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* at making python support for multiple images very easy. */
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cvaPoint resultPoint;
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cvautomationList curr;
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IplImage *rootImage;
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rootImage = cvLoadImage( rootImage_location, CV_LOAD_IMAGE_COLOR );
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int x = 0;
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for ( x = 0; x < listSize; x++ )
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{
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curr = subImageArray[x];
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if ( subImageArray[x].cvaImage != 0 )
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resultPoint = matchSubImage ( rootImage, curr.cvaImage, curr.searchMethod, curr.tolerance );
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else
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{
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/* We have a sub-image filename, go ahead and create the actual image. */
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IplImage *subImage;
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subImage = cvLoadImage( curr.fileName, CV_LOAD_IMAGE_COLOR );
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resultPoint = matchSubImage_center ( rootImage, subImage, curr.searchMethod, curr.tolerance );
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cvReleaseImage( &subImage );
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}
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curr.resultPoint = resultPoint;
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}
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cvReleaseImage( &rootImage );
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}
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