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We present in this paper a new approach for hand gesture analysis that allowsdigit recognition. The analysis is based on extracting a set of features from ahand image and then combining them by using an induction graph. The mostimportant features we extract from each image are the fingers locations, theirheights and the distance between each pair of fingers. Our approach consists ofthree steps: (i) Hand detection and localization, (ii) fingers extraction and(iii) features identification and combination to digit recognition. Each inputimage is assumed to contain only one person, thus we apply a fuzzy classifierto identify the skin pixels. In the finger extraction step, we attempt toremove all the hand components except the fingers, this process is based on thehand anatomy properties. The final step consists on representing histogram ofthe detected fingers in order to extract features that will be used for digitrecognition. The approach is invariant to scale, rotation and translation ofthe hand. Some experiments have been undertaken to show the effectiveness ofthe proposed approach.

A new approach for digit recognition based on hand gesture analysis