Implementing RoshamboGame System with Adaptive Skin Color Model

摘要

This paper utilizes the adaptive skin color model to design a roshambo game system under various light conditions. First, using an usb-webcam to capture the image of a hand, the hand gesture is identified through the method proposed by Holden [2]. The important point element of successfully identifying a hand gesture is using a skin color model to detect the complete contour of the hand. As image color is easily affected under different light sources, using a static skin color will yield errors. This study mainly explores the performance of Holden's method under various sources of light and references the RGB, HSV, and YCBCR models in different color spaces by several scholars to propose an adaptive skin color mo del. Experiment results found that this model performs well under low light(533lx) and decen tly under regular light. The experiment separates the background to find its' Y value to use the proper skin color model using the value's range. Finally the morphology of the closure (dilate once, erode thrice) is used to repair the border of the image to increase effect. Using adaptive skin color models, performance of low light was increased from 50% to 78% while other light sources achieved accurate rates of 85%~92%. The research results were used to create a robotic roshambo game system. The robot performs a relative interaction to roshambo results to achieve a fun and efficient system.