A Palmprint Recognition Algorithm Based on GIDBC

As fractal dimension could not describe the information of palmprint accurately as a characterization, differential box dimension (DBC) is improved by using a custom fractal operator, and a novel palmprint recognition algorithm based on Gabor transform and improved differential box dimension (GIDBC)...

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Bibliographic Details
Published inBiometric Recognition pp. 258 - 265
Main Authors Jia, Mengqi, Wei, Weibo, Hong, Danfeng, Wang, Gang
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
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Summary:As fractal dimension could not describe the information of palmprint accurately as a characterization, differential box dimension (DBC) is improved by using a custom fractal operator, and a novel palmprint recognition algorithm based on Gabor transform and improved differential box dimension (GIDBC) is proposed in this paper. Firstly, Gabor transform is used for palmprint images in frequency domain to get the information of multi-scale and multi-direction, and the ideas of block is used to divide palmprint images into blocks. Then every block’s feature vector is extracted by using improved differential box dimension (IDBC) algorithm, and features of all blocks are fused in the parallel. Finally, chi-square distance is used for classification. Compared with those traditional algorithms by experiments in PolyU palmprint database, recognition rate can reach 99.78%, feature extraction and matching time is 338ms, which demonstrates the validity and efficiency of the proposed algorithm.
ISBN:3319254162
9783319254166
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-25417-3_31