2012/01/19 by Bruno Brandoli Machado, Machado, Bruno Brandoli, Wesley Nunes Gonçalves +3
Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Medical Image Segmentation Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.1201.4139
Annals of Workshop of Computer Vision 2011
arxiv created 2012/01/19 · openalex publication_date 2012/01/19 · arxiv updated 2012/01/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Texture analysis is an important field of investigation that has received a great deal of interest from computer vision community. In this paper, we propose a novel approach for texture modeling based on partial differential equation (PDE). Each image f is decomposed into a family of derived sub-images. f is split into the u component, obtained with anisotropic diffusion, and the v component which is calculated by the difference between the original image and the u component. After enhancing the texture attribute v of the image, Gabor features are computed as descriptors. We validate the proposed approach on two texture datasets with high variability. We also evaluate our approach on an important real-world application: leaf-texture analysis. Experimental results indicate that our approach can be used to produce higher classification rates and can be successfully employed for different texture applications.