Implontation of Modern features detection and Matching Algorithms

Abstract

MO 73 Abstract In computer vision applications, key points-based features are important and frequently used in image processing algorithms. Several techniques were developed in literatures for features detection and matching, and each approach has some advantages and drawbacks. Harris corner detector is widely used in different engineering algorithms, and then comes SIFT (Scale Invariant Feature Transform) and SURF (Speeded-Up Robust Features) to overcome disadvantages of large-scale variation associated with Harris algorithm. Features matching techniques are of two important categories: one based on correlation and other based on descriptors. In this work, we propose the implementation of various key points’ detection and matching techniques on MATLAB Interface, the implemented graphical interface is easy to use for any users and does not require any learning. We have tested our implementation on different scenes of images, and we have done some discussions and conclusions.