SELECTION METHODS OF THE IMPORTANT CORNERS BASED ON ZERNIKE MOMENTS AND NEURAL NETWORKS
Zheng Dongfeng · Shandong Nongye Daxue xuebao · 2003
Corner selection plays an important role in the field of computer vision since the image corners include a large mount of useful information. The purpose of this paper is to study the selection method of the important corners in the given type of image. Firstly the image corners are obtained by using some type of image corners detection method, and then the more important corners are selected by using Zernike moments and neural networks. .The effectiveness of the new method is confirmed by the experiment in the end of this paper. Although the algorithm is only verified in some type of images, but it should be believed that the method can be extended to other similar situations.