The research of the wheel alignment system based on computer vision is a popular field for automobile safety. For realizing the effective and accurate feature recognition for the chessboard calibration target of the system, the enhancement algorithms based on Gamma correction are indicated. According to the research object, identification requires decreasing the pixel values in low grayscale and increasing the pixel values in high grayscale while keeping the pixels values in the middle grayscale. For this purpose, the novel Gamma correction curve is presented to enhance the target image. Experimental result shows that the enhancement method increases the contrast ratio of the chessboard target image which is benefit for feature extraction, points matching and vision measurement. Its effect and reliability meet the requirements of the detecting system for vehicle wheel alignment based on computer vision.