OpenCV - 图像拼接 [英] OpenCV - Image Stitching
问题描述
我正在使用以下代码拼接输入图像。对于未知的
原因，输出结果是垃圾！
似乎单应矩阵是错误的（或被错误地影响）
因为变换后的图像就像一个被利用的星！
我已经评论了我认为是问题来源的部分
但我无法实现。
任何帮助或点都是适当的！
I am using following code to stitch to input images. For an unknown reason the output result is crap! It seems that the homography matrix is wrong (or is affected wrongly) because the transformed image is like an "exploited star"! I have commented the part that I guess is the source of the problem but I cannot realize it. Any help or point is appriciated!
祝你有美好的一天，
阿里
Have a nice day, Ali
void Stitch2Image(IplImage *mImage1, IplImage *mImage2)
{
// Convert input images to gray
IplImage* gray1 = cvCreateImage(cvSize(mImage1->width, mImage1->height), 8, 1);
cvCvtColor(mImage1, gray1, CV_BGR2GRAY);
IplImage* gray2 = cvCreateImage(cvSize(mImage2->width, mImage2->height), 8, 1);
cvCvtColor(mImage2, gray2, CV_BGR2GRAY);
// Convert gray images to Mat
Mat img1(gray1);
Mat img2(gray2);
// Detect FAST keypoints and BRIEF features in the first image
FastFeatureDetector detector(50);
BriefDescriptorExtractor descriptorExtractor;
BruteForceMatcher<L1<uchar> > descriptorMatcher;
vector<KeyPoint> keypoints1;
detector.detect( img1, keypoints1 );
Mat descriptors1;
descriptorExtractor.compute( img1, keypoints1, descriptors1 );
/* Detect FAST keypoints and BRIEF features in the second image*/
vector<KeyPoint> keypoints2;
detector.detect( img1, keypoints2 );
Mat descriptors2;
descriptorExtractor.compute( img2, keypoints2, descriptors2 );
vector<DMatch> matches;
descriptorMatcher.match(descriptors1, descriptors2, matches);
if (matches.size()==0)
return;
vector<Point2f> points1, points2;
for(size_t q = 0; q < matches.size(); q++)
{
points1.push_back(keypoints1[matches[q].queryIdx].pt);
points2.push_back(keypoints2[matches[q].trainIdx].pt);
}
// Create the result image
result = cvCreateImage(cvSize(mImage2->width * 2, mImage2->height), 8, 3);
cvZero(result);
// Copy the second image in the result image
cvSetImageROI(result, cvRect(mImage2->width, 0, mImage2->width, mImage2->height));
cvCopy(mImage2, result);
cvResetImageROI(result);
// Create warp image
IplImage* warpImage = cvCloneImage(result);
cvZero(warpImage);
/************************** Is there anything wrong here!? *******************/
// Find homography matrix
Mat H = findHomography(Mat(points1), Mat(points2), 8, 3.0);
CvMat HH = H; // Is this line converted correctly?
// Transform warp image
cvWarpPerspective(mImage1, warpImage, &HH);
// Blend
blend(result, warpImage);
/*******************************************************************************/
cvReleaseImage(&gray1);
cvReleaseImage(&gray2);
cvReleaseImage(&warpImage);
}
推荐答案
这就是我的建议您按此顺序尝试：
This is what I would suggest you to try, in this order:
1）使用CV_RANSAC选项进行单应性。请参阅 http://opencv.willowgarage.com/documentation/cpp/calib3d_camera_calibration_and_3d_reconstruction.html
1) Use CV_RANSAC option for homography. Refer http://opencv.willowgarage.com/documentation/cpp/calib3d_camera_calibration_and_3d_reconstruction.html
2）尝试其他描述符，特别是OpenCV附带的SIFT或SURF。对于某些图像，FAST或BRIEF描述符不够区分。编辑（2012年8月）：ORB描述符基于BRIEF，非常好而且快速！
2) Try other descriptors, particularly SIFT or SURF which ship with OpenCV. For some images FAST or BRIEF descriptors are not discriminating enough. EDIT (Aug '12): The ORB descriptors, which are based on BRIEF, are quite good and fast!
3）尝试查看Homography矩阵（逐步完成）在调试模式或打印它）并查看它是否一致。
3) Try to look at the Homography matrix (step through in debug mode or print it) and see if it is consistent.
4）如果上面没有给你一个线索，试着看看形成的匹配。是否将一个图像中的一个点与另一个图像中的多个点匹配？如果是这样，问题应该再次出现在描述符或探测器上。
4) If above does not give you a clue, try to look at the matches that are formed. Is it matching one point in one image with a number of points in the other image? If so the problem again should be with the descriptors or the detector.
我的预感是描述符（因此1）或2）应修复它。）
My hunch is that it is the descriptors (so 1) or 2) should fix it).
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