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14 August 2019 Palmprint recognition based on local joint edge and orientation patterns
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Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791M (2019) https://doi.org/10.1117/12.2539645
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chunlan Fu, Yuxiang Chen, Huabin Wang, and Liang Tao "Palmprint recognition based on local joint edge and orientation patterns", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791M (14 August 2019); https://doi.org/10.1117/12.2539645
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