Techniques On Corner Points Detection And Image Matching

Techniques on corner points detection based on gray-level image and image matching method are presented in this thesis.Corners are image points that show a strong intensity change. The detection of corner points in images is essential for many tasks such as machine vision , image processing. The reason that this approach is so popular that corner points have a rich content of information, provide a sufficient constraint to vision processing and a reliable match between images, have a greatly improvement on computation speed. This thesis describes some previous algorithms on auto-correlation corner points detection. Then the performance analysis of these algorithms are given. An improved approach is presented in this paper on the basis of MIC(Minimum Intensity Change) algorithm. Experimental results show that the proposed algorithm has a better performance than the original one.Image matching is another important content of computer vision and image processing. It has been applied to many computer vision tasks. This thesis has made a comparison and list of many image matching algorithms and introduced some classic image matching methods in a detail. Finally the results of image matching are given in a form of experiments.