Apply SIFT and RANSAC on matrix[10X10]. Compare the results?

Answer 1

OpenCV has the function cv::findHomography which can optionally use RANSAC to find the homography matrix relating two images. You can see an example of this function in action here.

Specifically the section of code you are interested in is:

FlannBasedMatcher matcher;

std::vector< DMatch > matches;

matcher.match( descriptors_object, descriptors_scene, matches );

for( int i = 0; i < good_matches.size(); i++ )

{

//-- Get the keypoints from the good matches

obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );

scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );

}

Mat H = findHomography( obj, scene, CV_RANSAC );

You can then use the function cv::perspectiveTransform to warp the images according to the homography matrix.

Other options for cv::findHomography other than CV_RANSAC are 0 which uses every point and CV_LMEDS which uses the Least-Median method. More info can be found in the OpenCV camera calibration documentation here.