文件名称:
ASIFT+OpenCV图像特征匹配实战 - VC工程源码
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文件大小: 402kb
下载次数: 0
上传时间: 2012-10-16
详细说明: ASIFT+OpenCV图像特征匹配实战VC工程源码 OpenCV包含头文件: #include "cv.h" #include "highgui.h" #include "cxcore.h" 核心代码如下: if (!m_pImage1||!m_pImage2) { AfxMessageBox("please,select 2 images!"); return; } UpdateData(TRUE); CvSize sz1 = cvSize(m_pImage1->width,m_pImage1->height); CvSize sz2 = cvSize(m_pImage2->width,m_pImage2->height); CvScalar s; IplImage *gimg1 = cvCreateImage(sz1,IPL_DEPTH_8U,1); cvCvtColor(m_pImage1,gimg1,CV_BGR2GRAY); IplImage *gimg2 = cvCreat eImage(sz2,IPL_DEPTH_8U,1); cvCvtColor(m_pImage2,gimg2,CV_BGR2GRAY); size_t w1, h1; w1 = gimg1->width; h1 = gimg1->height; float * iarr1 = new float[w1*h1]; for(int i=0;i ipixels1(iarr1, iarr1 + w1 * h1); delete [] iarr1; size_t w2, h2; w2 = gimg2->width; h2 = gimg2->height; float * iarr2 = new float[w2*h2]; for(int i=0;i ipixels2(iarr2, iarr2 + w2 * h2); delete [] iarr2; float wS = IM_X; float hS = IM_Y; float zoom1=0, zoom2=0; int wS1=0, hS1=0, wS2=0, hS2=0; vector ipixels1_zoom, ipixels2_zoom; if (!m_bOrininal) { if (m_lWidth==0 || m_lHeight == 0) return; wS = m_lWidth; hS = m_lHeight; float InitSigma_aa = 1.6; float fproj_p, fproj_bg; char fproj_i; float *fproj_x4, *fproj_y4; int fproj_o; fproj_o = 3; fproj_p = 0; fproj_i = 0; fproj_bg = 0; fproj_x4 = 0; fproj_y4 = 0; float areaS = wS * hS; // Resize image 1 float area1 = w1 * h1; zoom1 = sqrt(area1/areaS); wS1 = (int) (w1 / zoom1); hS1 = (int) (h1 / zoom1); int fproj_sx = wS1; int fproj_sy = hS1; float fproj_x1 = 0; float fproj_y1 = 0; float fproj_x2 = wS1; float fproj_y2 = 0; float fproj_x3 = 0; float fproj_y3 = hS1; /* Anti-aliasing filtering along vertical direction */ if ( zoom1 > 1 ) { float sigma_aa = InitSigma_aa * zoom1 / 2; GaussianBlur1D(ipixels1,w1,h1,sigma_aa,1); GaussianBlur1D(ipixels1,w1,h1,sigma_aa,0); } // simulate a tilt: subsample the image along the vertical axis by a factor of t. ipixels1_zoom.resize(wS1*hS1); fproj (ipixels1, ipixels1_zoom, w1, h1, &fproj;_sx, &fproj;_sy, &fproj;_bg, &fproj;_o, &fproj;_p, &fproj;_i , fproj_x1 , fproj_y1 , fproj_x2 , fproj_y2 , fproj_x3 , fproj_y3, fproj_x4, fproj_y4); // Resize image 2 float area2 = w2 * h2; zoom2 = sqrt(area2/areaS); wS2 = (int) (w2 / zoom2); hS2 = (int) (h2 / zoom2); fproj_sx = wS2; fproj_sy = hS2; fproj_x2 = wS2; fproj_y3 = hS2; /* Anti-aliasing filtering along vertical direction */ if ( zoom1 > 1 ) { float sigma_aa = InitSigma_aa * zoom2 / 2; GaussianBlur1D(ipixels2,w2,h2,sigma_aa,1); GaussianBlur1D(ipixels2,w2,h2,sigma_aa,0); } // simulate a tilt: subsample the image along the vertical axis by a factor of t. ipixels2_zoom.resize(wS2*hS2); fproj (ipixels2, ipixels2_zoom, w2, h2, &fproj;_sx, &fproj;_sy, &fproj;_bg, &fproj;_o, &fproj;_p, &fproj;_i , fproj_x1 , fproj_y1 , fproj_x2 , fproj_y2 , fproj_x3 , fproj_y3, fproj_x4, fproj_y4); } else { ipixels1_zoom.resize(w1*h1); ipixels1_zoom = ipixels1; wS1 = w1; hS1 = h1; zoom1 = 1; ipixels2_zoom.resize(w2*h2); ipixels2_zoom = ipixels2; wS2 = w2; hS2 = h2; zoom2 = 1; } int num_of_tilts1 = m_lTilts1; int num_of_tilts2 = m_lTilts2; int verb = 0; // Define the SIFT parameters siftPar siftparameters; default_sift_parameters(siftparameters); vector< vector< keypointslist > > keys1; vector< vector< keypointslist > > keys2; int num_keys1=0, num_keys2=0; SetWindowText("Computing keypoints on the two images..."); CString str1,str2; time_t tstart, tend1,tend2; tstart = time(0); DWORD dstart = GetTickCount(); num_keys1 = compute_asift_keypoints(ipixels1_zoom, wS1, hS1, num_of_tilts1, verb, keys1, siftparameters); tend1 = time(0); m_lKeyNum1 = num_keys1; UpdateData(FALSE); str1.Format("Img1 Keypoints computation accomplished in %f s",difftime(tend1, tstart)); SetWindowText(str1); num_keys2 = compute_asift_keypoints(ipixels2_zoom, wS2, hS2, num_of_tilts2, verb, keys2, siftparameters); tend2 = time(0); m_lKeyNum2 = num_keys2; UpdateData(FALSE); str2.Format("Img2 Keypoints computation accomplished in %f s ,Matching the keypoints...",difftime(tend2, tstart)); SetWindowText(str2); //// Match ASIFT keypoints int num_matchings; matchingslist matchings; tstart = time(0); num_matchings = compute_asift_matches(num_of_tilts1, num_of_tilts2, wS1, hS1, wS2, hS2, verb, keys1, keys2, matchings, siftparameters); tend1 = time(0); DWORD dSpan = GetTickCount() - dstart; cout << "Keypoints matching accomplished in " << difftime(tend1, tstart) << " seconds." << endl; str2.Format("Keypoints matching accomplished in %f s",difftime(tend1, tstart)); SetWindowText(str2); m_lMatches = num_matchings; UpdateData(FALSE); str1.Format("Total time used:%d ms",dSpan); AfxMessageBox(str1); cvRelease((void**)&gimg1;); cvRelease((void**)&gimg2;); 参考网址:http://www.ipol.im/pub/art/2011/my-asift/ ...展开收缩
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