NDLI: Palmprint feature extraction using weight coding based non-negative sparse coding

Content Provider	IEEE Xplore Digital Library
Author	Li Shang Ming Cui Pin-gang Su Zhi-qiang Zhao Ji-xiang Du
Copyright Year	2010
Description	Author affiliation: Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou 215104 China (Li Shang; Ming Cui; Pin-gang Su; Zhi-qiang Zhao) \|\| Department of Computer Science and Technology, Huaqiao University, Quanzhou 362021 China, Department of Automation, University of Science and Technology of China, Hefei China (Ji-xiang Du)
Abstract	A novel palmprint feature extraction method is proposed by using the Weight Coding Based Non-negative Sparse Coding (WCBNNSC). The WCBNNSC algorithm can model the respective field of V1 in the primary visual system of brain. And this algorithm includes more image information than the early Non-negative Sparse Coding (NNSC). Utilizing the WCBNNSC algorithm, the feature basis vectors of palmprint images can be successfully learned. These features behave locality, orientation, and spatial selection, which is similar to the respective field feature of V1 in visual cortex. Further, using the features extracted, the palmprint reconstruction task can be successfully implemented. Moreover, compared with other palmprint feature extraction methods, simulation results show that our method proposed here is indeed efficient and useful in performing the feature extraction task of palmprint images.
Starting Page	1905
Ending Page	1908
File Size	369054
Page Count	4
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5647514
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Image coding image feature extraction Artificial neural networks Feature extraction non-negative sparse coding weight coding Image reconstruction Pixel Signal to noise ratio
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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