Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8517
Title: Hand shape recognition based on coherent distance shape contexts
Authors: Hu, RX
Jia, W
Zhang, D 
Gui, J
Song, LT
Keywords: Biometrics
Hand shape
Identification
Shape contexts
Verification
Issue Date: 2012
Publisher: Elsevier
Source: Pattern recognition, 2012, v. 45, no. 9, p. 3348-3359 How to cite?
Journal: Pattern recognition 
Abstract: In this paper, we propose a novel hand shape recognition method named as Coherent Distance Shape Contexts (CDSC), which is based on two classical shape representations, i.e., Shape Contexts (SC) and Inner-distance Shape Contexts (IDSC). CDSC has good ability to capture discriminative features from hand shape and can well deal with the inexact correspondence problem of hand landmark points. Particularly, it can extract features mainly from the contour of fingers. Thus, it is very robust to different hand poses or elastic deformations of finger valleys. In order to verify the effectiveness of CDSC, we create a new hand image database containing 4000 grayscale left hand images of 200 subjects, on which CDSC has achieved the accurate identification rate of 99.60% for identification and the Equal Error Rate of 0.9% for verification, which are comparable with the state-of-the-art hand shape recognition methods.
URI: http://hdl.handle.net/10397/8517
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2012.02.018
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