{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T17:23:05Z","timestamp":1793035385166,"version":"4.5.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T00:00:00Z","timestamp":1613779200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T00:00:00Z","timestamp":1613779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1007\/s11042-021-10646-0","type":"journal-article","created":{"date-parts":[[2021,2,21]],"date-time":"2021-02-21T00:05:40Z","timestamp":1613865940000},"page":"18839-18857","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":239,"title":["2D object recognition: a comparative analysis of SIFT, SURF and ORB feature descriptors"],"prefix":"10.1007","volume":"80","author":[{"given":"Monika","family":"Bansal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0115-1620","authenticated-orcid":false,"given":"Munish","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manish","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,2,20]]},"reference":[{"issue":"2","key":"10646_CR1","doi-asserted-by":"publisher","first-page":"55","DOI":"10.4236\/jdaip.2016.42005","volume":"4","author":"AKA Abdelmajed","year":"2016","unstructured":"Abdelmajed AKA (2016) A comparative study of locality preserving projection and principle component analysis on classification performance using logistic regression. J Data Anal Inform Process 4(2):55\u201363","journal-title":"J Data Anal Inform Process"},{"key":"10646_CR2","doi-asserted-by":"publisher","unstructured":"Bansal M, Kumar M, Kumar M (2020a) 2D object recognition techniques: state-of-the-art work. Arch Computation Methods Eng. https:\/\/doi.org\/10.1007\/s11831-020-09409-1","DOI":"10.1007\/s11831-020-09409-1"},{"key":"10646_CR3","doi-asserted-by":"publisher","unstructured":"Bansal M, Kumar M, Kumar M (2020b). XGBoost: object recognition using shape descriptors and extreme gradient boosting classifier. DOI: https:\/\/doi.org\/10.1007\/978-981-15-6876-3_16.","DOI":"10.1007\/978-981-15-6876-3_16"},{"issue":"3","key":"10646_CR4","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","volume":"110","author":"H Bay","year":"2008","unstructured":"Bay H, Ess A, Tuytelaars T, Van GL (2008) Speeded-up robust features (SURF). Comput Vis Image Underst 110(3):346\u2013359","journal-title":"Comput Vis Image Underst"},{"key":"10646_CR5","doi-asserted-by":"crossref","unstructured":"Bayraktar E, Boyraz P 2017 Analysis of feature detector and descriptor combinations with a localization experiment for various performance metrics. arXiv preprint arXiv:1710.06232","DOI":"10.3906\/elk-1602-225"},{"key":"10646_CR6","doi-asserted-by":"crossref","unstructured":"Bosch A, Zisserman A, Munoz X 2007 Image classification using random forests and ferns. Proceedings of the IEEE 11th International Conference on Computer Vision (ICCV), 1-8.","DOI":"10.1109\/ICCV.2007.4409066"},{"key":"10646_CR7","doi-asserted-by":"crossref","unstructured":"Calonder M, Lepetit V, Strecha C, Fua P 2010 BRIEF: binary robust independent elementary features. Proceedings of the European Conference on Computer Vision, 778-792.","DOI":"10.1007\/978-3-642-15561-1_56"},{"key":"10646_CR8","first-page":"1","volume-title":"Proceedings of the International Conference on Image and Vision Computing","author":"HJ Chien","year":"2016","unstructured":"Chien HJ, Chuang CC, Chen CY, Klette R (2016) When to use what feature? SIFT, SURF, ORB, or A-KAZE features for monocular visual odometry. In: Proceedings of the International Conference on Image and Vision Computing. IVCNZ, New Zealand, pp 1\u20136"},{"key":"10646_CR9","doi-asserted-by":"publisher","first-page":"34157","DOI":"10.1007\/s11042-019-08232-6","volume":"78","author":"S Gupta","year":"2019","unstructured":"Gupta S, Kumar M, Garg A (2019) Improved Object Recognition Results using SIFT and ORB Feature Detector. Multimed Tools Appl 78:34157\u201334171","journal-title":"Multimed Tools Appl"},{"key":"10646_CR10","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1007\/s10044-020-00879-4","volume":"23","author":"S Gupta","year":"2020","unstructured":"Gupta S, Roy PP, Dogra DP, Kim BG (2020) Retrieval of colour and texture images using local directional peak valley binary pattern. Pattern Anal Applic 23:1569\u20131585. https:\/\/doi.org\/10.1007\/s10044-020-00879-4","journal-title":"Pattern Anal Applic"},{"key":"10646_CR11","unstructured":"He X, Niyogi P (2004) Locality preserving projections. Adv Neural Inform Process Syst:153\u2013160"},{"key":"10646_CR12","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S and Sun J 2016 Deep residual learning for image recognition. In Proc IEEE Conf Comput Vis Pattern Recognition, 770-778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10646_CR13","doi-asserted-by":"crossref","unstructured":"Jayech K. Mahjoub MA 2017 Object recognition based on dynamic random forests and SURF descriptor. Proceedings of the International Conference on Intelligent Data Engineering and Automated Learning, 355-364.","DOI":"10.1007\/978-3-319-68935-7_39"},{"key":"10646_CR14","doi-asserted-by":"crossref","unstructured":"Jeong D M, Kim J H, Lee Y W and Kim B G 2018 Robust weighted Keypoint matching algorithm for image retrieval. Proc Second Int Conf Video, Image Processing:145-149.","DOI":"10.1145\/3301506.3301513"},{"issue":"5","key":"10646_CR15","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1007\/s00371-018-1503-0","volume":"35","author":"L Kabbai","year":"2019","unstructured":"Kabbai L, Abdellaoui M, Douik A (2019) Image classification by combining local and global features. Vis Comput 35(5):679\u2013693","journal-title":"Vis Comput"},{"key":"10646_CR16","unstructured":"Karami E, Prasad S and Shehata M 2017 Image matching using SIFT, SURF, BRIEF and ORB: performance comparison for distorted images. arXiv preprint arXiv:1710.02726"},{"key":"10646_CR17","unstructured":"Kim J, Kim BS, Savarese S 2012 Comparing image classification methods: K-nearest-neighbor and support-vector-machines. Appl Mathematics Electric Comput Eng 133-138."},{"key":"10646_CR18","doi-asserted-by":"publisher","first-page":"22741","DOI":"10.1007\/s11042-017-4344-3","volume":"76","author":"B Kim","year":"2017","unstructured":"Kim B, Hong G, Psannis KE (2017) Design of efficient shape feature for object-based watermarking technology. Multimed Tools Appl 76:22741\u201322759. https:\/\/doi.org\/10.1007\/s11042-017-4344-3","journal-title":"Multimed Tools Appl"},{"issue":"3","key":"10646_CR19","first-page":"164","volume":"3","author":"AV Kulkarni","year":"2013","unstructured":"Kulkarni AV, Jagtap JS, Harpale VK (2013) Object recognition with ORB and its implementation on FPGA. Int J Adv Comput Res 3(3):164","journal-title":"Int J Adv Comput Res"},{"key":"10646_CR20","doi-asserted-by":"crossref","unstructured":"Leutenegger S, Chli M, Siegwart R 2011 BRISK: binary robust invariant scalable Keypoints. Proceedings of the International Conference on Computer Vision (ICCV), 2548-2555.","DOI":"10.1109\/ICCV.2011.6126542"},{"key":"10646_CR21","doi-asserted-by":"crossref","unstructured":"Loussaief S, Abdelkrim A 2018 Deep learning vs. bag of features in machine learning for image classification. Proc Int Conf Adv Syst Electric Technol, 6-10","DOI":"10.1109\/ASET.2018.8379825"},{"issue":"2","key":"10646_CR22","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant Keypoints. Int J Comput Vis 60(2):91\u2013110","journal-title":"Int J Comput Vis"},{"issue":"3","key":"10646_CR23","first-page":"135","volume":"4","author":"DC Park","year":"2016","unstructured":"Park DC (2016) Image classification using Na\u00efve Bayes classifier. Int J Comput Sci Electronics Engineering (IJCSEE) 4(3):135\u2013139","journal-title":"Int J Comput Sci Electronics Engineering (IJCSEE)"},{"issue":"2","key":"10646_CR24","first-page":"38","volume":"11","author":"MP Patil","year":"2014","unstructured":"Patil MP, Kolhe SR (2014) Automatic image annotation using decision trees and rough sets. Int J Comput Sci Appl (IJCSA) 11(2):38\u201349","journal-title":"Int J Comput Sci Appl (IJCSA)"},{"key":"10646_CR25","doi-asserted-by":"crossref","unstructured":"Rosten E and Drummond T 2006 Machine learning for high speed corner detection. Proc 9th Eur Conf Comput Vision, 1:430\u2013443.","DOI":"10.1007\/11744023_34"},{"key":"10646_CR26","doi-asserted-by":"crossref","unstructured":"Rublee E, Rabaut V, Konolige K, Bradski G 2011 ORB: an efficient alternative to SIFT or SURF, Proceedings of the IEEE International Conference on Computer Vision (ICCV), 1-8","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"10646_CR27","doi-asserted-by":"crossref","unstructured":"Schroff F, Criminisi A, Zisserman A 2008 Object class segmentation using random forests. Proc British Machine Vision Assoc Conference (BMVC), 1-10.","DOI":"10.5244\/C.22.54"},{"issue":"3","key":"10646_CR28","first-page":"82","volume":"1","author":"J Shermina","year":"2010","unstructured":"Shermina J (2010) Application of locality preserving projections in face recognition. Int J Adv Comput Sci Appl 1(3):82\u201385","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"4","key":"10646_CR29","first-page":"378","volume":"1","author":"AM Shivakanth","year":"2014","unstructured":"Shivakanth AM (2014) Object recognition using SIFT. Int J Innovat Sci Eng Technol (IJISET) 1(4):378\u2013381","journal-title":"Int J Innovat Sci Eng Technol (IJISET)"},{"key":"10646_CR30","unstructured":"Simonyan K, Zisserman A 2014 Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556."},{"key":"10646_CR31","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1109\/ICCV.2005.77","volume":"1","author":"J Sivic","year":"2005","unstructured":"Sivic J, Russell BC, Efros AA, Zisserman A, Freeman WT (2005) Discovering objects and their location in images. Proc Tenth IEEE Int Conf Computer Vision 1:370\u2013377","journal-title":"Proc Tenth IEEE Int Conf Computer Vision"},{"issue":"11","key":"10646_CR32","doi-asserted-by":"publisher","first-page":"14129","DOI":"10.1007\/s11042-018-6793-8","volume":"78","author":"D Srivastava","year":"2019","unstructured":"Srivastava D, Bakthula R, Agarwal S (2019) Image classification using SURF and bag of LBP features constructed by clustering with fixed centers. Multimed Tools Appl 78(11):14129\u201314153","journal-title":"Multimed Tools Appl"},{"key":"10646_CR33","doi-asserted-by":"crossref","unstructured":"Tareen SAK, Saleem Z 2018 A comparative analysis of SIFT, SURF, KAZE, AKAZE, ORB, and BRISK. Proceedings of the International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 1-10","DOI":"10.1109\/ICOMET.2018.8346440"},{"key":"10646_CR34","doi-asserted-by":"crossref","unstructured":"Wang J, Yang J, Yu K, Lv F, Huang T, Gong Y 2010 Locality-constrained linear coding for image classification. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 3360-3367","DOI":"10.1109\/CVPR.2010.5540018"},{"issue":"4","key":"10646_CR35","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1587\/transinf.2016EDL8167","volume":"100","author":"F Yang","year":"2017","unstructured":"Yang F, XIE M (2017) Codebook learning for image recognition based on parallel key SIFT analysis. IEICE Trans Inf Syst 100(4):927\u2013930","journal-title":"IEICE Trans Inf Syst"},{"key":"10646_CR36","first-page":"2126","volume":"2","author":"H Zhang","year":"2006","unstructured":"Zhang H, Berg AC, Maire M, Malik J (2006) SVM-KNN: discriminative nearest neighbor classification for visual category recognition. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2:2126\u20132136","journal-title":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10646-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-10646-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10646-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T09:28:22Z","timestamp":1621502902000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-10646-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,20]]},"references-count":36,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["10646"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-10646-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,20]]},"assertion":[{"value":"24 June 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 February 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 February 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no conflict of interest in this work. The authors have considered a public dataset, namely, Caltech-101 for experimental work.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}}]}}