Gesture Recognition Algorithm Based On The Geometric Characteristics Of Study

Hand gestures play a natural and intuitive communication mode for all human dialogs. With the development of computer technology, HCI(Human Computer Interaction) is advancing and human is becoming the center in HCI. So a growing number of researcher are concerning the study on hand gesture recognition. However, vision-based recognition of hand gestures is an extremely challenging interdisciplinary project due to following three reasons: (1) hand gestures are rich in diversities, multi-meanings, and space-time varieties; (2) human hands are complex non-rigid objects; (3) computer vision itself is an ill-posed problem. Hand gestures include dynamic hand gestures, whose meanings are based on the track of the motion of hands, and static hand gestures in which the shape of hand gesture is used to express the meaning. This paper, as a part of the researching subject, the algorithm of hand gesture recognition and synthesizing, is supported by shanghai nature and science fund, tries to perform study on static hand gesture recognition.Hand gesture recognition is composed of three parts, preprocessing hand gesture images, extracting image features and recognition. During the preprocessing, image smoothing, then image sharpening are performed on standard hand gesture images (128*128 pixels gray bmp image). Finally, binary image is extracted and contour is detected by means of 8-connected boundary tracking when necessary.In the part of feature extraction and recognition, this paper presents two methods based on geometric features: Algorithm by Using HDC for Feature Pixels and Algorithm Based on Invariant Moment and Edge Detection. In the Algorithm by Using HDC for Feature Pixels, the contour of hand gesture, which will be regarded as a curve, is extracted after preprocessing. Then a scale space of the curve is created by the application of the hierarchical discrete correlation. Anew method which is based on the motion of the curve through scale space is proposed for feature detection. Finally, gesture patterns are recognized by means of minimal distance of feature pixels. In Algorithm Based on Invariant Moment and Edge Detection, an algorithm based on two featuresof invariant moment and edge detection is presented. After preprocessing, binary image is obtained and then 4 from 7 invariant moments are extracted. By edge detection, histogram is formed to describe the edge information. Finally, the recognition is performed on 30 letter gestures by computing distance, in which different coefficients are set to these two features.The recognition rate of is 83.3% in Algorithm by Using HDC for Feature Pixels by performing recognition on 30 hand gestures. In Algorithm Based on Invariant Moment and Edge Detection, the recognition rate of 91.3% is achieved.Yangqing He(Computer Software and Theory)Directed by-. Yuan Ge...