标题:Palmprint recognition algorithm with horizontally expanded blanket dimension
作者:Guo, Xiumei; Zhou, Weidong; Wang, Yu
作者机构:[Guo, Xiumei; Zhou, Weidong; Wang, Yu] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.; [Guo, Xiumei] Shandong Agr Univ, Sch 更多
通讯作者:Zhou, W
通讯作者地址:[Zhou, WD]Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.
来源:NEUROCOMPUTING
出版年:2014
卷:127
页码:152-160
DOI:10.1016/j.neucom.2013.08.027
关键词:Fractal dimension; Blanket dimension; Palmprint recognition; Feature; extraction
摘要:As an emerging biometric technology, palmprint recognition has been extensively researched due to its easy collection, user friendliness, high verification accuracy and reliability. Blanket dimension is a commonly used fractal dimension and has the multi-resolution characteristics with which the image texture information can be better extracted. In this work, palmprint recognition with blanket dimension and its expansions was investigated. The efficiencies of horizontally and vertically expanded blanket dimensions for extracting the directional feature of palmprint were compared, and a palmprint recognition algorithm based on horizontally expanded blanket dimension (HEBD) was proposed according to the comparison results. Furthermore, a multi-scale HEBD (MHEBD) algorithm for palmprint recognition was also presented, and the MHEBD was demonstrated to be more effective than the single-scale HEBD for feature extraction. The algorithm was evaluated on Hong Kong Polytechnic University (PolyU) database (v2) and CASIA database. The experimental results indicate that the multi-scale HEBD can extract the palmprint features effectively and efficiently with a high recognition rate and less processing time. (C) 2013 Elsevier B.V. All rights reserved.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:10
Scopus被引频次:12
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84888434145&doi=10.1016%2fj.neucom.2013.08.027&partnerID=40&md5=fb1e92e1739b1eeef003d85d1ff1ea5b
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