Based On Geometric Moments Of Gesture Recognition Algorithm

The Research of Gesture-Language can be applied in many fields such as Computer Access Gesture-Language Teaching, TV Bilingual Broadcasting, the search of Virtual Human. The search of Gesture-Language includes the following subjects : Teaching, Computer Graphology, Robot Motion and Physic etc. It is a very meaningful subject. The Search of Gesture Recognition has a wide range of applications such as : the communication between the deaf and the normal, the access recognition of voice recognition ,the control of VR, the study of robot.This article gives a method of Gesture Recognition based on Statistics. We can apply the Geometric Moment in the Feature Extraction. We can solve the problem of Recognition brought by rotation and scale.The Gesture Recognition mainly includes the following process: Image preprocessing, feature extraction, pattern recognition.In the process of image preprocessing there are several image operations such as image smooth, image sharpen and image segment. We use the template operation in the process of image smoothing, laplacian operator hi the process of image sharpening and maximum variance method in the process of Region segment.Feature Extraction is vital to Gesture Recognition. The uncertainty of rotation, scale of gesture brings many difficulties to the extraction of feature. Geometric Moment is a arithmetic based on statistics. This article applys the arithmetic in the extraction of gesture feature. The feature can remains the same when the image rotating and scaling.In the process of constructing the sample lib, we collected three sets of Chinese Letter Gesture. Two sets were used to machine learning, the third was used to test the recognition rate the Gesture Recognition System.The Recognition Process includes the following phases: firstly, image preprocessing; secondly , feature extraction ;finally, matching with the Standard Gesture Lib. The Gesture which has the minimum Distance to the Input Gesture is theRecognition Result-In the experiment, I used 30 Chinese Pinyin gestures and 10 Arabic number gestures, the cumulate recognition rate is up to 93 %.Tao YinDirected by -.Yuan Ge...