Research on Skin Color Image Post-processing Methods for Gesture Recognition System

Abstract

Abstract: Skin color region image post-processing methods suitable for gesture recognition system based on computer vision was proposed. To solve the problem of face and hand often occur simultaneously in the image frame, the training process and grouping strategy of AdaBoost face detector based on Haar-like template were studied, and a rapid culling method of face region based on fusion of color information was proposed. To reduce the influence of noise in skin color region image, impulse noise suppression and skin-like region rejection was proposed. The test results have shown that the proposed methods can greatly speed up the face detection process under the premise of detection accuracy almost remaining unchanged, and significantly improve the accuracy of subsequent hand posture recognition steps.

Key words: gesture recognition, skin detection, face detection, noise suppression

CLC Number:

TP391.9

Wang Renda, Yin Yong, Xing Shengwei. Research on Skin Color Image Post-processing Methods for Gesture Recognition System[J]. Journal of System Simulation, 2015, 27(10): 2483-2488.

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