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ABSTRACT

In this paper we address the issue of hand contour segmentation from digital images using deformable contour models (snakes). We present a novel variation of the traditional snake solution, where additional nodes are inserted and redundant nodes are deleted to better describe the complexity of the extracted line. Candidate locations for node insertion and deletion are based on an analysis of the energy terms in the snake solution. This allows us to use more closely spaced nodes along the high curvature segments of a hand outline. This dynamic manipulation of the node number and spacing within a single snake allows us to better capture the geometry of the hand and accommodate its radiometric behavior. Here we present our approach, and some experimental results demonstrating its performance as a tool for hand contour segmentation in biometrics, medical imaging, and pattern recognition.



KEYWORDS

Biometrics, deformable models, hand contour, image segmentation.

ARCHIVES
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THE INTERNATIONAL JOURNAL OF FORENSIC COMPUTER SCIENCE - IJoFCS

Volume 1, Number 1, pp 10-18, DOI: 10.5769/J200601001 or  http://dx.doi.org/10.5769/J200601001


A Deformable Contour Based Approach for Hand Image Segmentation

By Marcos d'Ornellas 


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