{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T06:44:22Z","timestamp":1778827462413,"version":"3.51.4"},"reference-count":15,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2013,3,18]],"date-time":"2013-03-18T00:00:00Z","timestamp":1363564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Region of Interest (ROI) extraction is a crucial step in an automatic finger vein recognition system. The aim of ROI extraction is to decide which part of the image is suitable for finger vein feature extraction. This paper proposes a finger vein ROI extraction method which is robust to finger displacement and rotation. First, we determine the middle line of the finger, which will be used to correct the image skew. Then, a sliding window is used to detect the phalangeal joints and further to ascertain the height of ROI. Last, for the corrective image with certain height, we will obtain the ROI by using the internal tangents of finger edges as the left and right boundary. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods, and thus improve the performance of finger vein identification system. Besides, to acquire the high quality finger vein image during the capture process, we propose eight criteria for finger vein capture from different aspects and these criteria should be helpful to some extent for finger vein capture.<\/jats:p>","DOI":"10.3390\/s130303799","type":"journal-article","created":{"date-parts":[[2013,3,18]],"date-time":"2013-03-18T13:58:38Z","timestamp":1363615118000},"page":"3799-3815","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Sliding Window-Based Region of Interest Extraction for  Finger Vein Images"],"prefix":"10.3390","volume":"13","author":[{"given":"Lu","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gongping","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yilong","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongyang","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5793","DOI":"10.1016\/j.eswa.2008.07.042","article-title":"Driver identification using finger-vein patterns with Radon transform and neural network","volume":"36","author":"Wu","year":"2009","journal-title":"Expert Syst. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.jnca.2009.12.006","article-title":"Finger vein recognition with manifold learning","volume":"33","author":"Liu","year":"2010","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_3","unstructured":"Hashimoto, J. (2006, January 15\u201317). Finger Vein Authentication Technology and Its Future. Honolulu, HI, USA."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Pi, W., Shin, J., and Park, D. (2010, January 1\u20133). An Effective Quality Improvement Approach for Low Quality Finger Vein Image. Kyoto, Japan.","DOI":"10.1109\/ICEIE.2010.5559667"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"11357","DOI":"10.3390\/s111211357","article-title":"Finger vein recognition using local line binary pattern","volume":"11","author":"Rosdi","year":"2011","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1016\/j.patrec.2012.04.018","article-title":"Finger-vein ROI localization and vein ridge enhancement","volume":"33","author":"Yang","year":"2012","journal-title":"Patt. Recogn. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yang, J.F., and Li, X. (2010, January 23\u201326). Efficient Finger Vein Localization and Recognition. Tianjin, China.","DOI":"10.1109\/ICPR.2010.287"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1109\/TIP.2011.2171697","article-title":"Human identification using finger images","volume":"21","author":"Ajay","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.3390\/s110302319","article-title":"New finger biometric method using near infrared imaging","volume":"11","author":"Lee","year":"2011","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1007\/s00138-004-0149-2","article-title":"Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification","volume":"15","author":"Miura","year":"2004","journal-title":"Mach. Vis. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1738","DOI":"10.3390\/s120201738","article-title":"Finger vein recognition based on a personalized best bit map","volume":"12","author":"Yang","year":"2012","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1016\/j.optlaseng.2011.03.004","article-title":"Image restoration of skin scattering and optical blurring for finger vein recognition","volume":"49","author":"Lee","year":"2011","journal-title":"Opt. Lasers Eng."},{"key":"ref_13","first-page":"324","article-title":"Finger vein image quality assessment method","volume":"6","author":"Wang","year":"2011","journal-title":"CAAI Trans. Intell. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1185","DOI":"10.1093\/ietisy\/e90-d.8.1185","article-title":"Extraction of finger-vein patterns using maximum curvature points in image profiles","volume":"E90-D","author":"Miura","year":"2007","journal-title":"IEICE Trans. Inform. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Huang, B.N., Dai, Y.G., Li, R.F., Tang, D.R., and Li, W.X. (2010, January 23\u201326). Finger-Vein Authentication Based on Wide Line Detector and Pattern Normalization. Istanbul, Turkey.","DOI":"10.1109\/ICPR.2010.316"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/3\/3799\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:45:36Z","timestamp":1760219136000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/3\/3799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,3,18]]},"references-count":15,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2013,3]]}},"alternative-id":["s130303799"],"URL":"https:\/\/doi.org\/10.3390\/s130303799","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,3,18]]}}}