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Proceedings Paper

Palmprint recognition based on local joint edge and orientation patterns
Author(s): Chunlan Fu; Yuxiang Chen; Huabin Wang; Liang Tao
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Paper Abstract

Aiming at the characteristics of edge gradient features and orientation features of palmprint images, a new Local Joint Edge and Orientation Patterns (LJEOP) method is proposed to extract palmprint features. Firstly, the Kirsch operator utilizes calculate the edge response values of palmprint images in 8 different orientations and the Local Maximum Edge Pattern(LMEP) is proposed to represent the edge features. The orientation features of the palmprint image are extracted by using a Gabor filter or a Modified Finite Radon Transform (MFRAT). Then the joint analysis of edge features and orientation features is carried out to construct a two-dimensional feature matrix. Compared with some existing palmprint recognition methods, our experimental results on the MSpalmprint library achieve higher recognition rate ,lower equal error rate and faster recognition speed.

Paper Details

Date Published: 14 August 2019
PDF: 9 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791M (14 August 2019); doi: 10.1117/12.2539645
Show Author Affiliations
Chunlan Fu, Anhui Univ. (China)
Yuxiang Chen, Anhui Univ. (China)
Huabin Wang, Anhui Univ. (China)
Liang Tao, Anhui Univ. (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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