Hand localization and fingers features extraction: application to digit recognition in sign language

Authors:
A. Ben Jmaa;W. Mahdi;Y. Ben Jemaa;A. Ben Hamadou
Affiliations:
Multimedia, InfoRmation systems and Advanced Computing Laboratory, Tunisia;Multimedia, InfoRmation systems and Advanced Computing Laboratory, Tunisia;Signal and System Research Unit, Tunisia;Multimedia, InfoRmation systems and Advanced Computing Laboratory, Tunisia
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

We present in this paper an approach of hand gesture analysis that aims at recognizing a digit. The analysis is based on extracting a set of features from a hand image and then combining them by using an induction graph. The most important features we extract from each image are the fingers locations, their heights and the distance between each pair of fingers. Our approach consists of three steps: (i) Hand localization, (ii) fingers extraction and (iii) features identification and combination to digit recognition. Each input image is assumed to contain only one hand with black background, thus we apply a classifier based on one skin color to identify the skin pixels. In the finger extraction step, we attempt to remove all the hand components except the fingers, this process is based on the hand anatomy properties. The final step is based on histogram representation of the detected fingers which results in the features identification, which results in the digit recognition. The approach is invariant to scale, rotation and translation of the hand. Some experiments have been undertaken to show the effectivness of the proposed approach.