Geometric Feature Extraction for Hand Gesture Recognition

Computer applications have been spread ubiquitous due to its essential important that facilitate our daily life, gesture system is one of the most appealing applications that dependents mainly on exploiting the right features that can embody the entire gesture and give the correct meaning of that gesture. For constructing gesture recognition system a serial steps should be considered that are: segmentation the hand, hand gesture modeling, features extraction stage, and finally gestures classification. This work concerned with the representation of the extracted features, the important features should be extracted so that to introduce a full and correct portray of the gesture in the feature space to enable the classifier model to recognize the gesture correctly, and in this work two features are extracted. Experimental results show that the extracted features are effective, robust, and can cover the entire feature space of the selected gestures.