NDLI: Hand geometry pattern recognition through Gaussian mixture modelling

Content Provider	IEEE Xplore Digital Library
Author	Sanchez-Reillo, R.
Copyright Year	2000
Description	Author affiliation: ETSI Telecomunicacion, Univ. Politecnica de Madrid, Spain (Sanchez-Reillo, R.)
Abstract	Gaussian mixture modelling (GMM) is a statistical pattern recognition technique usually applied to speaker identification. This technique can be used with morphological features extracted from images. Therefore, this technique is applied to hand geometry biometrics in order to improve the results obtained with other verification techniques. This biometric technique, which is considered to be a low-medium security one, can be applied to high security environments due to its error rates below 5%. The features to enter the GMM algorithm can be extracted from a color image of the hand (both the top and the side view of it). This image can then be processed and its edge detected before a morphological analysis is performed, thus obtaining a feature vector as small as 12 bytes. In this paper, after a short introduction and a general overview of the GMMs, the whole process is explained.
Starting Page	937
Ending Page	940
File Size	405443
Page Count	4
File Format	PDF
ISBN	0769507506
ISSN	10514651
DOI	10.1109/ICPR.2000.906228
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-09-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Pattern recognition Biometrics Security Image edge detection Feature extraction Error analysis Color Image analysis Performance analysis
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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