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Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information
Joint Authors
Zhang, Baoqing
Mu, Zhichun
Zeng, Hui
Luo, Shuang
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-24
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Orientation information is critical to the accuracy of ear recognition systems.
In this paper, a new feature extraction approach is investigated for ear recognition by using orientation information of Gabor wavelets.
The proposed Gabor orientation feature can not only avoid too much redundancy in conventional Gabor feature but also tend to extract more precise orientation information of the ear shape contours.
Then, Gabor orientation feature based nonnegative sparse representation classification (Gabor orientation + NSRC) is proposed for ear recognition.
Compared with SRC in which the sparse coding coefficients can be negative, the nonnegativity of NSRC conforms to the intuitive notion of combining parts to form a whole and therefore is more consistent with the biological modeling of visual data.
Additionally, the use of Gabor orientation features increases the discriminative power of NSRC.
Extensive experimental results show that the proposed Gabor orientation feature based nonnegative sparse representation classification paradigm achieves much better recognition performance and is found to be more robust to challenging problems such as pose changes, illumination variations, and ear partial occlusion in real-world applications.
American Psychological Association (APA)
Zhang, Baoqing& Mu, Zhichun& Zeng, Hui& Luo, Shuang. 2014. Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1048404
Modern Language Association (MLA)
Zhang, Baoqing…[et al.]. Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1048404
American Medical Association (AMA)
Zhang, Baoqing& Mu, Zhichun& Zeng, Hui& Luo, Shuang. Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1048404
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048404