Abstract: Reading recognition methods of the pointer type meter were vulnerable to illumination variation, and the accuracy was not high. This paper presents a pointer instrument reading method based on visual saliency regions detection. In detail, the proposed approach firstly utilizes the visual prior knowledge of saliency region detection(including region contrast, spatial relationships, the center priori et al.) to outstand meter pointer region, then optimizes extracted region by undirected ranking function to suppress interference of non-pointer region and highlight the pointer region. Secondly, the presented method successively rotates meter pointer image, and calculates the maximum value of the projection on the vertical axis in different rotated angles to obtain the rotated angle which rotates the pointer parallel to the horizontal axis. Next, the algorithm rotates meter image to make the pointer paralleling to the horizontal axis, and extracts the top and bottom part pointer region, and determines the maximum projection position on a horizontal axis, and then obtains the pointer deflection angle. Finally, meter reading is derived by using the least squares method to fit a linear function between the pointer deflection angle and the meter scale. Experimental results show that the proposed method can better extract pointer region in different illumination, the error between meter readings and manual reading is smaller, and the algorithm is stable and reliable.