Flexible Edge Component Detection Using Image Power Spectrum Sparsity

Abstract

A novel method for edge component detection based on image power spectrum sparsity is presented. The edge size can be varied by changing the block size and threshold parameter to obtain the desired edge component. The image is first divided into sub-blocks and the power spectrum sparsity for each sub-block is calculated. On the basis of the image power spectrum sparsity value, each block is verified by the threshold value to determine the edge component. The experimental results show that the proposed method is suitable for object tracking because of the novel feature of the flexible edge size, which can dramatically reduce the amount of data to be stored.