The paper reports our study of image stabilization in a camera emulation system. In the study, a way of dealing with optical image stabilization is proposed to cope with blurring images caused by hand shake. The idea of the proposed image stabilization is to determine possible hand-shake situations based on the proposed rules and then to correct blurring image through position fuzzy control compensation. This method directly detects motion signals and employs a rule based mechanism to distinguish possible hand shake situations from normal camera movements. If a hand-shake situation is determined, the corresponding correction signal is generated to correct the image in a real-time fashion. In order to demonstrate the effectiveness of the proposed approach, in our implementation, the system directly moves the camera mounted on an X-Y platform to compensate the hand shake effects. Some statistics of the phenomena of the actual system are observed to form the scheme proposed in this study. From our experiments, the average percentage of shake reduction is 54.64%. It is clearly evident that this method indeed can have better image quality.