opencv源程序surf算法

///* // * A Demo to OpenCV Implementation of SURF // * Further Information Refer to "SURF: Speed-Up Robust Feature" // * Author: Liu Liu // * liuliu.1987+opencv@gmail.com // */ // //#include <cv.h> //#include <highgui.h> //#include <ctype.h> //#include <stdio.h> //#include <stdlib.h> // //#include <iostream> //#include <vector> // //using namespace std; // // //// define whether to use approximate nearest-neighbor search //#define USE_FLANN // // //IplImage *image = 0; // //double //compareSURFDescriptors( const float* d1, const float* d2, double best, int length ) //{ // double total_cost = 0; // assert( length % 4 == 0 ); // for( int i = 0; i < length; i += 4 ) // { // double t0 = d1[i] - d2[i]; // double t1 = d1[i+1] - d2[i+1]; // double t2 = d1[i+2] - d2[i+2]; // double t3 = d1[i+3] - d2[i+3]; // total_cost += t0*t0 + t1*t1 + t2*t2 + t3*t3; // if( total_cost > best ) // break; // } // return total_cost; //} // // //int //naiveNearestNeighbor( const float* vec, int laplacian, // const CvSeq* model_keypoints, // const CvSeq* model_descriptors ) //{ // int length = (int)(model_descriptors->elem_size/sizeof(float)); // int i, neighbor = -1; // double d, dist1 = 1e6, dist2 = 1e6; // CvSeqReader reader, kreader; // cvStartReadSeq( model_keypoints, &kreader, 0 ); // cvStartReadSeq( model_descriptors, &reader, 0 ); // // for( i = 0; i < model_descriptors->total; i++ ) // { // const CvSURFPoint* kp = (const CvSURFPoint*)kreader.ptr; // const float* mvec = (const float*)reader.ptr; // CV_NEXT_SEQ_ELEM( kreader.seq->elem_size, kreader ); // CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader ); // if( laplacian != kp->laplacian ) // continue; // d = compareSURFDescriptors( vec, mvec, dist2, length ); // if( d < dist1 ) // { // dist2 = dist1; // dist1 = d; // neighbor = i; // } // else if ( d < dist2 ) // dist2 = d; // } // if ( dist1 < 0.6*dist2 ) // return neighbor; // return -1; //} // //void //findPairs( const CvSeq* objectKeypoints, const CvSeq* objectDescriptors, // const CvSeq* imageKeypoints, const CvSeq* imageDescriptors, vector<int>& ptpairs ) //{ // int i; // CvSeqReader reader, kreader; // cvStartReadSeq( objectKeypoints, &kreader ); // cvStartReadSeq( objectDescriptors, &reader ); // ptpairs.clear(); // // for( i = 0; i < objectDescriptors->total; i++ ) // { // const CvSURFPoint* kp = (const CvSURFPoint*)kreader.ptr; // const float* descriptor = (const float*)reader.ptr; // CV_NEXT_SEQ_ELEM( kreader.seq->elem_size, kreader ); // CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader ); // int nearest_neighbor = naiveNearestNeighbor( descriptor, kp->laplacian, imageKeypoints, imageDescriptors ); // if( nearest_neighbor >= 0 ) // { // ptpairs.push_back(i); // ptpairs.push_back(nearest_neighbor); // } // } //} // // //void //flannFindPairs( const CvSeq*, const CvSeq* objectDescriptors, // const CvSeq*, const CvSeq* imageDescriptors, vector<int>& ptpairs ) //{ // int length = (int)(objectDescriptors->elem_size/sizeof(float)); // // cv::Mat m_object(objectDescriptors->total, length, CV_32F); // cv::Mat m_image(imageDescriptors->total, length, CV_32F); // // // // copy descriptors // CvSeqReader obj_reader; // float* obj_ptr = m_object.ptr<float>(0); // cvStartReadSeq( objectDescriptors, &obj_reader ); // for(int i = 0; i < objectDescriptors->total; i++ ) // { // const float* descriptor = (const float*)obj_reader.ptr; // CV_NEXT_SEQ_ELEM( obj_reader.seq->elem_size, obj_reader ); // memcpy(obj_ptr, descriptor, length*sizeof(float)); // obj_ptr += length; // } // CvSeqReader img_reader; // float* img_ptr = m_image.ptr<float>(0); // cvStartReadSeq( imageDescriptors, &img_reader ); // for(int i = 0; i < imageDescriptors->total; i++ ) // { // const float* descriptor = (const float*)img_reader.ptr; // CV_NEXT_SEQ_ELEM( img_reader.seq->elem_size, img_reader ); // memcpy(img_ptr, descriptor, length*sizeof(float)); // img_ptr += length; // } // // // find nearest neighbors using FLANN // cv::Mat m_indices(objectDescriptors->total, 2, CV_32S); // cv::Mat m_dists(objectDescriptors->total, 2, CV_32F); // cv::flann::Index flann_index(m_image, cv::flann::KDTreeIndexParams(4)); // using 4 randomized kdtrees // flann_index.knnSearch(m_object, m_indices, m_dists, 2, cv::flann::SearchParams(64) ); // maximum number of leafs checked // // int* indices_ptr = m_indices.ptr<int>(0); // float* dists_ptr = m_dists.ptr<float>(0); // for (int i=0;i<m_indices.rows;++i) { // if (dists_ptr[2*i]<0.6*dists_ptr[2*i+1]) { // ptpairs.push_back(i); // ptpairs.push_back(indices_ptr[2*i]); // } // } //} // // ///* a rough implementation for object location */ //int //locatePlanarObject( const CvSeq* objectKeypoints, const CvSeq* objectDescriptors, // const CvSeq* imageKeypoints, const CvSeq* imageDescriptors, // const CvPoint src_corners[4], CvPoint dst_corners[4] ) //{ // double h[9]; // CvMat _h = cvMat(3, 3, CV_64F, h); // vector<int> ptpairs; // vector<CvPoint2D32f> pt1, pt2; // CvMat _pt1, _pt2; // int i, n; // //#ifdef USE_FLANN // flannFindPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs ); //#else // findPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs ); //#endif // // n = ptpairs.size()/2; // if( n < 4 ) // return 0; // // pt1.resize(n); // pt2.resize(n); // for( i = 0; i < n; i++ ) // { // pt1[i] = ((CvSURFPoint*)cvGetSeqElem(objectKeypoints,ptpairs[i*2]))->pt; // pt2[i] = ((CvSURFPoint*)cvGetSeqElem(imageKeypoints,ptpairs[i*2+1]))->pt; // } // // _pt1 = cvMat(1, n, CV_32FC2, &pt1[0] ); // _pt2 = cvMat(1, n, CV_32FC2, &pt2[0] ); // if( !cvFindHomography( &_pt1, &_pt2, &_h, CV_RANSAC, 5 )) // return 0; // // for( i = 0; i < 4; i++ ) // { // double x = src_corners[i].x, y = src_corners[i].y; // double Z = 1./(h[6]*x + h[7]*y + h[8]); // double X = (h[0]*x + h[1]*y + h[2])*Z; // double Y = (h[3]*x + h[4]*y + h[5])*Z; // dst_corners[i] = cvPoint(cvRound(X), cvRound(Y)); // } // // return 1; //} // //int main(int argc, char** argv) //{ // const char* object_filename = argc == 3 ? argv[1] : "beaver.png"; // const char* scene_filename = argc == 3 ? argv[2] : "box.png"; // // CvMemStorage* storage = cvCreateMemStorage(0); // // cvNamedWindow("Object", 1); // cvNamedWindow("Object Correspond", 1); // // static CvScalar colors[] = // { // {{0,0,255}}, // {{0,128,255}}, // {{0,255,255}}, // {{0,255,0}}, // {{255,128,0}}, // {{255,255,0}}, // {{255,0,0}}, // {{255,0,255}}, // {{255,255,255}} // }; // // IplImage* object = cvLoadImage( object_filename, CV_LOAD_IMAGE_GRAYSCALE ); // IplImage* image = cvLoadImage( scene_filename, CV_LOAD_IMAGE_GRAYSCALE ); // if( !object || !image ) // { // fprintf( stderr, "Can not load %s and/or %s\n" // "Usage: find_obj [<object_filename> <scene_filename>]\n", // object_filename, scene_filename ); // exit(-1); // } // IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3); // cvCvtColor( object, object_color, CV_GRAY2BGR ); // // CvSeq *objectKeypoints = 0, *objectDescriptors = 0; // CvSeq *imageKeypoints = 0, *imageDescriptors = 0; // int i; // CvSURFParams params = cvSURFParams(500, 1); // // double tt = (double)cvGetTickCount(); // c