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Proceedings Paper

Ear recognition based on force field feature extraction and convergence feature extraction
Author(s): Jiajia Luo; Zhichun Mu; Yu Wang
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Paper Abstract

Ear recognition based on the force field transform is new and effective. Three different applications of the force field transform were discussed in this paper. Firstly, we discussed the problem in the process of potential wells extraction and overcame the contradiction between the continuity of the force field and the discreteness of intensity images. Secondly, an improved convergence-based ear recognition method was presented in this paper. To overcome the problem of threshold segmentation, an adaptive threshold segmentation method was used to find the threshold automatically; to reduce the computational complexity, a quick classification was realized by combining the Canny-operator and the Modified Hausdorff Distance (MHD). Finally, the algebraic property of force field was combined with Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) together to obtain feature vectors for ear recognition. We tested these applications of the force field transform on two ear databases. Experimental results show the validity and robustness of the force field transform for ear recognition.

Paper Details

Date Published: 13 October 2008
PDF: 6 pages
Proc. SPIE 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence, 71272E (13 October 2008); doi: 10.1117/12.806740
Show Author Affiliations
Jiajia Luo, Univ. of Science and Technology Beijing (China)
Zhichun Mu, Univ. of Science and Technology Beijing (China)
Yu Wang, Univ. of Science and Technology Beijing (China)


Published in SPIE Proceedings Vol. 7127:
Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence

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