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Texture Object Segmentation Based on Affine Invariant Texture Detection

2017/12/23 by Jianwei Zhang, Xu Chen, Zhang, Jianwei +3
Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image Retrieval and Classification Techniques #Image and Video Processing (eess.IV) #Medical Image Segmentation Techniques #cs.CV #eess.IV #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1712.08776

6pages, 15 figures

arxiv created 2017/12/23 · openalex publication_date 2017/12/23 · arxiv updated 2017/12/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

To solve the issue of segmenting rich texture images, a novel detection methods based on the affine invariable principle is proposed. Considering the similarity between the texture areas, we first take the affine transform to get numerous shapes, and utilize the KLT algorithm to verify the similarity. The transforms include rotation, proportional transformation and perspective deformation to cope with a variety of situations. Then we propose an improved LBP method combining canny edge detection to handle the boundary in the segmentation process. Moreover, human-computer interaction of this method which helps splitting the matched texture area from the original images is user-friendly.

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