OpenCV2简单的特征匹配

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特征的匹配大致可以分为3个步骤：

特征的提取
计算特征向量
特征匹配

对于3个步骤，在OpenCV2中都进行了封装。所有的特征提取方法都实现FeatureDetector接口，DescriptorExtractor接口则封装了对特征向量（特征描述符）的提取，而所有特征向量的匹配都继承了DescriptorMatcher接口。

surf

int main(){    const string imgName1 = "x://image//01.jpg";    const string imgName2 = "x://image//02.jpg";    Mat img1 = imread(imgName1);    Mat img2 = imread(imgName2);    if (!img1.data || !img2.data)        return -1;    //step1: Detect the keypoints using SURF Detector    int minHessian = 400;    SurfFeatureDetector detector(minHessian);    vector<KeyPoint> keypoints1, keypoints2;    detector.detect(img1, keypoints1);    detector.detect(img2, keypoints2);    //step2: Calculate descriptors (feature vectors)    SurfDescriptorExtractor extractor;    Mat descriptors1, descriptors2;    extractor.compute(img1, keypoints1, descriptors1);    extractor.compute(img2, keypoints2, descriptors2);    //step3:Matching descriptor vectors with a brute force matcher    BFMatcher matcher(NORM_L2);    vector<DMatch> matches;    matcher.match(descriptors1, descriptors2,matches);    //Draw matches    Mat imgMatches;    drawMatches(img1, keypoints1, img2, keypoints2, matches, imgMatches);    namedWindow("Matches");    imshow("Matches", imgMatches);    waitKey();    return 0;}

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