NDLI: Sign Language Finger Alphabet Recognition from Gabor-PCA Representation of Hand Gestures

Content Provider	IEEE Xplore Digital Library
Author	Amin, M.A. Hong Yan
Copyright Year	2007
Description	Author affiliation: City Univ. of Hong Kong, Kowloon (Amin, M.A.; Hong Yan)
Abstract	During recent years a large number of computer aided applications have been developed to help the disabled people. This has improved the communication between the able and the hearing impaired community. An intelligent signed alphabet recognizer can work as an aiding agent to translate the signs to words (and also sentences) and vice versa. To achieve this goal few steps to be followed, among which the first complicated task is to recognize the sign-language alphabets from hand gesture images. In this paper, we propose a system that is able to recognize American Sign Language (ASL) alphabets from hand gesture with average 93.23% accuracy. The classification is performed with fuzzy-c-mean clustering on a lower dimensional data which is acquired from the Principle Component Analysis (PCA) of Gabor representation of hand gesture images. Out of the top 20 Principle Components (PCs) the best combination of PCs is determined by finding the best fuzzy cluster for the corresponding PCs of the training data. The best result is obtained from the combination of the fourth to seventh principle components.
Starting Page	2218
Ending Page	2223
File Size	4447081
Page Count	6
File Format	PDF
ISBN	9781424409723
DOI	10.1109/ICMLC.2007.4370514
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handicapped aids Fingers Personal communication networks Computer applications Application software Auditory system Intelligent agent Image recognition Image analysis Performance analysis Clustering algorithm Sign language Finger alphabet recognition Gabor wavelet PCA
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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