在我的OpenCV的项目,我想检测的图像复制伪造的举动。我知道如何使用opencv FLANN在2个不同的图像中进行特征匹配,但是我对如何使用FLANN检测图像中的复制移动伪造变得非常困惑。如何使用OpenCV的特征匹配检测复制伪造移动
P.S1:我得到的筛关键点和形象的描述,并卡在使用特征匹配类。
P.S2:特征匹配的类型不是对我很重要。
在此先感谢。
更新:
这些图片是什么,我需要
一个例子,有一个相匹配两幅图像的特征并做一些喜欢它的代码两个图像(没有一个),在机器人的OpenCV本地格式的代码是象下面这样:
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);
显示你当前的代码和您正在使用图像的样本肯定是有帮助的。 – alexisrozhkov
@ user3896254谢谢你的建议,我编辑自己的帖子,并添加例子和代码 – Evil