匹配模板图像(缩放)到主/更大的图像 [英] Matching template imge(scaled) to Main/larger image

问题描述

我想在主图像中查找/检查子图像/模板图像并想知道它的坐标，

I want to find/check subImage/template image in main image and want to know its coordinates,

我已经使用下面链接中给出的代码来实现它，

I have used code given at following link to implement it,

检查 iOS 中图像中是否存在子图像

如果模板图像的大小与较大图像的匹配部分的大小完全相同，则可以正常工作.

It is working fine, if the size of the template image is exactly same as size of the matching part of larger image.

但是，如果子图像被缩小或放大而不是匹配较大图像的一部分，则无法正确给出结果.

But it is not giving result properly if the subimage is scaled down or scaled up than matching part of larger image.

推荐答案

使用 OpenCV 特征检测.它比模板匹配更准确..

Use OpenCV Feature Detection. it is more accurate than template matching..

请尝试使用此代码..

-(void)featureDetection:(UIImage*)largerImage withImage:(UIImage*)subImage
{
    cv::Mat tempMat1 = [largerImage CVMat];
    cv::Mat tempMat2 = [subImage CVMat];

    cv::cvtColor(tempMat1, tempMat1, CV_RGB2GRAY);
    cv::cvtColor(tempMat2, tempMat2, CV_RGB2GRAY);

    if( !tempMat1.data || !tempMat2.data ) {
        return;
    }

    //-- Step 1: Detect the keypoints using SURF Detector
    int minHessian = 25;

    cv::SurfFeatureDetector detector( minHessian ); // More Accurate bt take more time..
    //cv::FastFeatureDetector detector( minHessian ); //Less Accurate bt take less time..

    std::vector<cv::KeyPoint> keypoints_1, keypoints_2;

    detector.detect( tempMat1, keypoints_1 );
    detector.detect( tempMat2, keypoints_2 );

    //-- Step 2: Calculate descriptors (feature vectors)
    cv::SurfDescriptorExtractor extractor;

    cv::Mat descriptors_1, descriptors_2;

    extractor.compute( tempMat1, keypoints_1, descriptors_1 );
    extractor.compute( tempMat2, keypoints_2, descriptors_2 );

    std::vector<cv::Point2f> obj_corners(4);

    //Get the corners from the object
    obj_corners[0] = (cvPoint(0,0));
    obj_corners[1] = (cvPoint(tempMat2.cols,0));
    obj_corners[2] = (cvPoint(tempMat2.cols,tempMat2.rows));
    obj_corners[3] = (cvPoint(0, tempMat2.rows));

    //-- Step 3: Matching descriptor vectors with a brute force matcher
    //cv::BruteForceMatcher < cv::L2<float> > matcher;
    cv::FlannBasedMatcher matcher;
    //std::vector< cv::DMatch > matches;
    std::vector<cv::vector<cv::DMatch > > matches;

    std::vector<cv::DMatch > good_matches;
    std::vector<cv::Point2f> obj;
    std::vector<cv::Point2f> scene;
    std::vector<cv::Point2f> scene_corners(4);
    cv::Mat H;

    matcher.knnMatch( descriptors_2, descriptors_1, matches,2);

    for(int i = 0; i < cv::min(tempMat1.rows-1,(int) matches.size()); i++)  {

        if((matches[i][0].distance < 0.6*(matches[i][1].distance)) && ((int) matches[i].size()<=2 && (int) matches[i].size()>0))  {
            good_matches.push_back(matches[i][0]);
        }
    }
    cv::Mat img_matches;
    drawMatches( tempMat2, keypoints_2, tempMat1, keypoints_1, good_matches, img_matches );

    NSLog(@"good matches %lu",good_matches.size());

    if (good_matches.size() >= 4)  {

         for( int i = 0; i < good_matches.size(); i++ ) {
             //Get the keypoints from the good matches
             obj.push_back( keypoints_2[ good_matches[i].queryIdx ].pt );
             scene.push_back( keypoints_1[ good_matches[i].trainIdx ].pt );
         }

         H = findHomography( obj, scene, CV_RANSAC );

         perspectiveTransform( obj_corners, scene_corners, H);

         NSLog(@"%f %f",scene_corners[0].x,scene_corners[0].y);
         NSLog(@"%f %f",scene_corners[1].x,scene_corners[1].y);
         NSLog(@"%f %f",scene_corners[2].x,scene_corners[2].y);
         NSLog(@"%f %f",scene_corners[3].x,scene_corners[3].y);


         //Draw lines between the corners (the mapped object in the scene image )
         line( tempMat1, scene_corners[0], scene_corners[1], cvScalar(0, 255, 0), 4 );

         line( tempMat1, scene_corners[1], scene_corners[2], cvScalar( 0, 255, 0), 4 );

         line( tempMat1, scene_corners[2], scene_corners[3], cvScalar( 0, 255, 0), 4 );

         line( tempMat1, scene_corners[3], scene_corners[0], cvScalar( 0, 255, 0), 4 );
     }

     // View matching..

     UIImage *resultimage = [UIImage imageWithCVMat:img_matches];
     UIImageView *imageview = [[UIImageView alloc] initWithImage:resultimage];
     imageview.frame = CGRectMake(0, 0, 320, 240);
     [self.view addSubview:imageview];

     // View Result

     UIImage *resultimage2 = [UIImage imageWithCVMat:tempMat1];
     UIImageView *imageview2 = [[UIImageView alloc] initWithImage:resultimage2];
     imageview2.frame = CGRectMake(0, 240, 320, 240);
     [self.view addSubview:imageview2];
}

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