{"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/brain-inspired-robust-delineation-operator","title":"Brain-inspired robust delineation operator","arxiv_id":"1811.10240","date":"2018-11-26","proceeding":null,"authors":["Nicola Strisciuglio","George Azzopardi","Nicolai Petkov"],"abstract":"In this paper we present a novel filter, based on the existing COSFIRE\nfilter, for the delineation of patterns of interest. It includes a mechanism of\npush-pull inhibition that improves robustness to noise in terms of spurious\ntexture. Push-pull inhibition is a phenomenon that is observed in neurons in\narea V1 of the visual cortex, which suppresses the response of certain simple\ncells for stimuli of preferred orientation but of non-preferred contrast. This\ntype of inhibition allows for sharper detection of the patterns of interest and\nimproves the quality of delineation especially in images with spurious texture.\n  We performed experiments on images from different applications, namely the\ndetection of rose stems for automatic gardening, the delineation of cracks in\npavements and road surfaces, and the segmentation of blood vessels in retinal\nimages. Push-pull inhibition helped to improve results considerably in all\napplications.","url_abs":"http://arxiv.org/abs/1811.10240v1","url_pdf":"http://arxiv.org/pdf/1811.10240v1.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":"brain-inspired-robust-delineation-operator","repo_url":"https://gitlab.com/nicstrisc/RUSTICO","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}