Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/220
Title: Personal recognition using hand shape and texture
Authors: Pathak, AK
Zhang, DD 
Keywords: Biometrics
Feature level fusion
Feature subset selection and combination
Hand-shape recognition
Palmprint recognition
Issue Date: Aug-2006
Publisher: IEEE
Source: IEEE transactions on image processing, Aug. 2006, v. 15, no. 8, p.2454-2461 How to cite?
Journal: IEEE transactions on image processing 
Abstract: This paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), k-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems.
URI: http://hdl.handle.net/10397/220
ISSN: 1057-7149
DOI: 10.1109/TIP.2006.875214
Rights: © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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