An Improved Corner Detector Based on the Skeleton for Texture Image
Jinda Liu, Hongxing Pei · Pattern Recognition and Image Analysis · 2021
Abstract Texture analysis is a significant area in image processing, but feature point extraction is pretty susceptible to noise in texture images. In this paper, a new method for extracting feature points, especially from the paper overlapping images, is presented, which is using dynamic threshold, mathematical morphology and image thinning to extract potential feature points. And an optimization algorithm is also proposed to promote the repeatability of feature points via analyzing corresponding skeletons. Results show that the proposed algorithm could depress noise, and the repeatability of this method (60%) outperforms traditional feature extraction algorithms, like Harris (46%), FAST (57%), and SUSAN (45%), in paper overlapping images.