Study of Corner Detection Algorithms and Evaluation Methods
Interest points are widely used in computer vision applications such as camera calibration, robot localization and object tracking that require fast and efficient feature matching. A large number of techniques have been proposed in the literature. Such comparative study is crucial for specific applications. It is always necessary to understand the advantages and disadvantages of the existing techniques so that best possible ones can be selected. In this paper a study of Harris, Moravec and SUSAN Corner detection Algorithms has been done for obtaining features required to track and recognize objects in an image. Corner detection of noisy images is a challenging task in image processing. Natural images often get corrupted by noise during acquisition and transmission. As Corner detection of these noisy images does not provide desired results, hence de noising is required.