SIFT特征具有缩放、旋转特征不变性,下载了大牛的matlab版SIFT特征提取代码,解释如下:
1.调用方法:
将文件加入matlab目录后,在主程序中有两种操作:
op1:寻找图像中的Sift特征:
[image, descrips, locs] = sift('scene.pgm'); showkeys(image, locs);
match('scene.pgm','book.pgm');
由于scene和book两图中有相同的一本书,但orientation和size都不同,可以发现所得结果中Sift特征检测结果非常好。
2.代码下载地址:
http://www.cs.ubc.ca/~lowe/keypoints/
3.想用自己的图片进行调用:
i1=imread('D:\Images\New\Cars\image_0001.jpg'); i2=imread('D:\Images\New\Cars\image_0076.jpg'); i11=rgb2gray(i1); i22=rgb2gray(i2); imwrite(i11,'v1.jpg','quality',80); imwrite(i22,'v2.jpg','quality',80); match('v1.jpg','v2.jpg');
experiment results:
scene
book
compare result
EXP2:
C代码:
// FeatureDetector.cpp : Defines the entry point for the console application. // #include "stdafx.h" #include "highgui.h" #include "cv.h" #include "vector" #include "opencv\cxcore.hpp" #include "iostream" #include "opencv.hpp" #include "nonfree.hpp" #include "showhelper.h" using namespace cv; using namespace std; int _tmain(int argc, _TCHAR* argv[]) { //Load Image Mat c_src1 = imread( "..\\Images\\3.jpg"); Mat c_src2 = imread("..\\Images\\4.jpg"); Mat src1 = imread( "..\\Images\\3.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat src2 = imread( "..\\Images\\4.jpg", CV_LOAD_IMAGE_GRAYSCALE); if( !src1.data || !src2.data ) { std::cout<< " --(!) Error reading images " << std::endl; return -1; } //sift feature detect SiftFeatureDetector detector; std::vector<KeyPoint> kp1, kp2; detector.detect( src1, kp1 ); detector.detect( src2, kp2 ); SiftDescriptorExtractor extractor; Mat des1,des2;//descriptor extractor.compute(src1,kp1,des1); extractor.compute(src2,kp2,des2); Mat res1,res2; int drawmode = DrawMatchesFlags::DRAW_RICH_KEYPOINTS; drawKeypoints(c_src1,kp1,res1,Scalar::all(-1),drawmode);//在内存中画出特征点 drawKeypoints(c_src2,kp2,res2,Scalar::all(-1),drawmode); cout<<"size of description of Img1: "<<kp1.size()<<endl; cout<<"size of description of Img2: "<<kp2.size()<<endl; BFMatcher matcher(NORM_L2); vector<DMatch> matches; matcher.match(des1,des2,matches); Mat img_match; drawMatches(src1,kp1,src2,kp2,matches,img_match);//,Scalar::all(-1),Scalar::all(-1),vector<char>(),drawmode); cout<<"number of matched points: "<<matches.size()<<endl; imshow("matches",img_match); cvWaitKey(); cvDestroyAllWindows(); return 0; }
Python代码:
http://blog.csdn.net/abcjennifer/article/details/7639681
关于sift的其他讲解:
http://blog.csdn.net/abcjennifer/article/details/7639681
http://blog.csdn.net/abcjennifer/article/details/7372880
http://blog.csdn.net/abcjennifer/article/details/7365882
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