{"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/image-matching-using-sift-surf-brief-and-orb","title":"Image Matching Using SIFT, SURF, BRIEF and ORB: Performance Comparison for Distorted Images","arxiv_id":"1710.02726","date":"2017-10-07","proceeding":null,"authors":["Ebrahim Karami","Siva Prasad","Mohamed Shehata"],"abstract":"Fast and robust image matching is a very important task with various\napplications in computer vision and robotics. In this paper, we compare the\nperformance of three different image matching techniques, i.e., SIFT, SURF, and\nORB, against different kinds of transformations and deformations such as\nscaling, rotation, noise, fish eye distortion, and shearing. For this purpose,\nwe manually apply different types of transformations on original images and\ncompute the matching evaluation parameters such as the number of key points in\nimages, the matching rate, and the execution time required for each algorithm\nand we will show that which algorithm is the best more robust against each kind\nof distortion. Index Terms-Image matching, scale invariant feature transform\n(SIFT), speed up robust feature (SURF), robust independent elementary features\n(BRIEF), oriented FAST, rotated BRIEF (ORB).","url_abs":"http://arxiv.org/abs/1710.02726v1","url_pdf":"http://arxiv.org/pdf/1710.02726v1.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":"image-matching-using-sift-surf-brief-and-orb","repo_url":"https://github.com/cvankir2/nsf_auburn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}