{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fwlbp-a-scale-invariant-descriptor-for","title":"FWLBP: A Scale Invariant Descriptor for Texture Classification","arxiv_id":"1801.03228","date":"2018-01-10","proceeding":null,"authors":["Swalpa Kumar Roy","Nilavra Bhattacharya","Bhabatosh Chanda","Bidyut. B. Chaudhuri","Dipak Kumar Ghosh"],"abstract":"In this paper we propose a novel texture descriptor called Fractal Weighted\nLocal Binary Pattern (FWLBP). The fractal dimension (FD) measure is relatively\ninvariant to scale-changes, and presents a good correlation with human\nviewpoint of surface roughness. We have utilized this property to construct a\nscale-invariant descriptor. Here, the input image is sampled using an augmented\nform of the local binary pattern (LBP) over three different radii, and then\nused an indexing operation to assign FD weights to the collected samples. The\nfinal histogram of the descriptor has its features calculated using LBP, and\nits weights computed from the FD image. The proposed descriptor is scale\ninvariant, and is also robust in rotation or reflection, and partially tolerant\nto noise and illumination changes. In addition, the local fractal dimension is\nrelatively insensitive to the bi-Lipschitz transformations, whereas its\nextension is adequate to precisely discriminate the fundamental of texture\nprimitives. Experiment results carried out on standard texture databases show\nthat the proposed descriptor achieved better classification rates compared to\nthe state-of-the-art descriptors.","url_abs":"http://arxiv.org/abs/1801.03228v2","url_pdf":"http://arxiv.org/pdf/1801.03228v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fwlbp-a-scale-invariant-descriptor-for","repo_url":"https://github.com/swalpa/FWLBP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"texture-classification","task_name":"Texture Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}