在我的opencv项目中,我想要检测图像中的复制移动伪造。我知道如何使用opencv FLANN进行2个不同图像的特征匹配,但是我对如何在图像中使用FLANN进行复制移动伪造检测感到困惑。
附注1:我获取了图像的SIFT关键点和描述符,并卡在使用特征匹配类上。
附注2:特征匹配的类型对我来说不重要。
提前致谢。
更新:
这些图片是我需要的示例。
附注1:我获取了图像的SIFT关键点和描述符,并卡在使用特征匹配类上。
附注2:特征匹配的类型对我来说不重要。
提前致谢。
更新:
这些图片是我需要的示例。
以下是一段匹配两张图像特征并在两张图像上执行类似操作的代码(不是单张图像),这段代码是以Android原生OpenCV格式编写的:
vector<KeyPoint> keypoints;
Mat descriptors;
// Create a SIFT keypoint detector.
SiftFeatureDetector detector;
detector.detect(image_gray, keypoints);
LOGI("Detected %d Keypoints ...", (int) keypoints.size());
// Compute feature description.
detector.compute(image, keypoints, descriptors);
LOGI("Compute Feature ...");
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors, descriptors, matches );
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors.rows; i++ )
{ double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
printf("-- Max dist : %f \n", max_dist );
printf("-- Min dist : %f \n", min_dist );
//-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist,
//-- or a small arbitary value ( 0.02 ) in the event that min_dist is very
//-- small)
//-- PS.- radiusMatch can also be used here.
std::vector< DMatch > good_matches;
for( int i = 0; i < descriptors.rows; i++ )
{ if( matches[i].distance <= max(2*min_dist, 0.02) )
{ good_matches.push_back( matches[i]); }
}
//-- Draw only "good" matches
Mat img_matches;
drawMatches( image, keypoints, image, keypoints,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Show detected matches
// imshow( "Good Matches", img_matches );
imwrite(imgOutFile, img_matches);