This study proposes a method for using stereo vision and face recogonition. The method differs from the feedback detection method used in sensors in general. The method disregards unimportant environmental changes and improves the overall performance of the recognition and tracking functions. Dual-CCD cameras on the visual system are used to capture images of faces. Through image preprocessing, determination of the moving target, and the position of the target center, the image is matched with the sample image to allow the robot to recognize and track stereo objects visually. The robot can recognize and track faces. And, the system also sends the images to a remote computer by wireless. A scheme is proposed to enhance the authentication messages by hash function in wireless communications. Since the proposed scheme provides an encryption function, it improves the authentication for wireless communications. 1. Introduction The information technology industry has vigorously developed, and computer vision has increased in importance. The advancement of computer technology has directed increasing attention to CPU and DSP. In addition, the annual decline in hardware cost has significantly reduced the computation time and cost of image processing and has thus increased the practicality of computer vision systems and their applications. Although such systems have greatly improved in terms of the theory, algorithms, and practical applications of image processing, core technologies of computer vision still require breakthroughs and innovation. For instance, if a leaf falls on a moving car, computer vision should not mistake the leaf as an obstacle and put the car on break or turn it around [1–5]. Controlling data transmission in a wireless environment and to prevent illegal access to resources, users must be authorized [6]. Privacy is an important subject in wireless communications. Users require protection from identifying theft or being caught in some way. Thus, the anonymous technology is a solution to solve the problems of user’s identification that could be stolen by attackers. The features of chaos systems include their dynamic response and high sensitivity to variations in the initial values of a system, such as nonperiodicity, nonconvergence, and control parameters. Many methodologies and profound mathematical theories about chaos systems have been proposed in applications such as image encryption [7–9], secure communications [10, 11], and image processing [12, 13] in the past 20 years. Huang et al. [7] proposed a scheme for implementing quasioptimal
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