Computer Vision-Based Static Hand Gesture Recognition System

Camera can catch the information naturally expressed by people such as eye movements, expression, gesture and motion. For users, communicatingwith computers by camera is efficient and natural. It can provide a convenient addition to user-computer dialogues and reduce the obstacle to use computer. Recent years espacially, with the development of computer science, research on new human-computer interaction technology become extremely active, and advancement has been achieved. These research includes face recognition, expression recognition, hand gesture regognition, pose recognition and so on.Hand gesture is a natural and straight human-computer interactionmethod. There are two methods on hand gesture recognition, recognition based on data glove and recogniton based on computer vision. Take hand as the input equipment directly, communication between human and computer will need no more other intermediate media. Users can control the machines around simply sign to it with the hand gesture user itself defines. However, gesture has the characters of multi-mode, multi-meaning and has discrepancy undercertain time and space situation; moreover, human handsare complicated transformed objects and there is visual instability, all of which make gesture recognition based on computer sight become a challengeable multi-subject researchgoal.This paper realized a static hand gesture recognition system based on computer vision. This system can recognize 10 common static hand gestures inputted from camera at real time. It is a real-time system, so both recognition time and the correctrecognition rate have to be considerd while designing the system. In the aspect of hand gesture modeling, the system adopt hand gesture model basedon apparent; In the aspect of hand gesture analysis, the system picks up eightcharacters through image preprocess and character extraction; In the aspect of recognition, the system adopts two times classifation (rough classification and particular classification).The system consists of three part. First, preprocession of the originalhand gesture image, in this part hand area is extracted from background through the character of human complexion, and then the system gets the edge through noise smoothing and Laplacian edge extraction; Second, extraxction of hand gesture characters, in this part the system extracts eight characters as an eigenvector; Third, the real-time procession to the Video Capture Card (天敏SDK-2000) , in this part the system processes the real-time data inputted from camera with a callback function and find the single image of static hand gesture.