{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:45:08Z","timestamp":1760240708121,"version":"build-2065373602"},"reference-count":20,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2019,8,28]],"date-time":"2019-08-28T00:00:00Z","timestamp":1566950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673021"],"award-info":[{"award-number":["61673021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The dorsal hand vein images captured by cross-device may have great differences in brightness, displacement, rotation angle and size. These deviations must influence greatly the results of dorsal hand vein recognition. To solve these problems, the method of dorsal hand vein recognition was put forward based on bit plane and block mutual information in this paper. Firstly, the input gray image of dorsal hand vein was converted to eight-bit planes to overcome the interference of brightness inside the higher bit planes and the interference of noise inside the lower bit planes. Secondly, the texture of each bit plane of dorsal hand vein was described by a block method and the mutual information between blocks was calculated as texture features by three kinds of modes to solve the problem of rotation and size. Finally, the experiments cross-device were carried out. One device was used to be registered, the other was used to recognize. Compared with the SIFT (Scale-invariant feature transform, SIFT) algorithm, the new algorithm can increase the recognition rate of dorsal hand vein from 86.60% to 93.33%.<\/jats:p>","DOI":"10.3390\/s19173718","type":"journal-article","created":{"date-parts":[[2019,8,28]],"date-time":"2019-08-28T11:23:18Z","timestamp":1566991398000},"page":"3718","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information"],"prefix":"10.3390","volume":"19","author":[{"given":"Yiding","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Communication Engineering, School of Information, North China University of Technology, No. 5, Jinyuanzhuang Road, Shijingshan District, Beijing 100043, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6160-3997","authenticated-orcid":false,"given":"Heng","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Communication Engineering, School of Information, North China University of Technology, No. 5, Jinyuanzhuang Road, Shijingshan District, Beijing 100043, China"}]},{"given":"Xiaochen","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Communication Engineering, School of Information, North China University of Technology, No. 5, Jinyuanzhuang Road, Shijingshan District, Beijing 100043, China"}]},{"given":"Yuanyan","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, School of Technology, University of Macau, Macau 999078, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2599","DOI":"10.1109\/TIFS.2017.2713340","article-title":"Quality-specific hand vein recognition system","volume":"12","author":"Wang","year":"2017","journal-title":"IEEE Trans. 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