The reliability of computer vision applications highly depends on the extraction of compact, fast, and accurate and robust feature description. This paper presents a better and modified binary descriptor based on ORB (oriented and rotated brief) with the SVM-RBF-RFE (support vector machine-radial basis function-recursive feature elimination) to achieve a better extraction and representation of local binary descriptors. This work presents the extensive comparison of the proposed modified descriptor with the state-of-the-art binary descriptors on various datasets. The results show that the proposed descriptor is highly distinctive and efficient as compared to the other state-of-the-art binary descriptors. The experiments were performed on the four benchmark datasets PASCAL, CALTECH, COIL, and OXFORD to demonstrate the robustness and effectiveness of the proposed descriptor. The robustness and effectiveness of the proposed descriptor is tested under the various transformations like scaling, rotation, noise, intensity variation.<\/p>","DOI":"10.4018\/jitr.2021010102","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T15:06:26Z","timestamp":1611587186000},"page":"20-36","source":"Crossref","is-referenced-by-count":1,"title":["A Modified Binary Descriptor for Object Detection"],"prefix":"10.4018","volume":"14","author":[{"given":"Ritu","family":"Rani","sequence":"first","affiliation":[{"name":"HMR Institute of Technology and Management, India"}]},{"given":"Ravinder","family":"Kumar","sequence":"additional","affiliation":[{"name":"Skill Faculty of Engineering, Shri Vishwakarma Skill University, India"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8675-6903","authenticated-orcid":true,"given":"Amit Prakash","family":"Singh","sequence":"additional","affiliation":[{"name":"Guru Gobind Singh Indraprastha University, Delhi, India"}]}],"member":"2432","container-title":["Journal of Information Technology Research"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=271405","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T23:52:54Z","timestamp":1651881174000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/JITR.2021010102"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2021,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"URL":"https:\/\/doi.org\/10.4018\/jitr.2021010102","relation":{},"ISSN":["1938-7857","1938-7865"],"issn-type":[{"value":"1938-7857","type":"print"},{"value":"1938-7865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,1]]}}}