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A continuous path performed by the hand in a period of time is considered for the purpose of gesture recognition. Dynamic gestures recognition is a complex topic since it spans from the conventional method of separating the hand from surrounding environment to searching for the fingers and palm. This paper proposes a strategy of hand recognition using a PC webcam, a segmentation technique (HS-ab which means HSV and CIELab color space), pre-processing of images to reduce noise and a classifier such as Principle Components Analysis (PCA) for the detection and tracking of the hand of the user. The results show that the segmentation technique HS-ab and the method PCA are robust in the execution of the system, although there are various conditions such as illumination, speed and precision of the movements. It is for this reason that a suitable extraction and classification of features allows the location of the gesture. The system was tested with the database of the training images and has a 94.74% accuracy.

Recognition of a Single Dynamic Gesture with the Segmentation Technique HS-ab and Principle Components Analysis (PCA)