Aiming at the problems of low accuracy and complex calculation in existing subpixel edge location algorithm, a subpixel edge location algorithm is proposed based on Gauss integral curved surface fitting. According to the characteristic of unilateral step edge, the edge normal section line Gauss integral model is constructed, on the basis of determining edge transition zone, the pixel information in fitting curved surface area is transformed into the active coordinates of edge curve, and the transformed pixel coordinates and gray information are fitted according to Gauss integral model, the accurate subpixel edge of the image is located. With the vision measurement system described in this paper, the experiment on the gauge block line edge was conducted, and the result was compared with that for traditional Gauss curved surface fitting subpixel edge location algorithm. The result proves that the subpixel edge location algorithm based on Gauss integral curved surface fitting has high location accuracy, the linear error of the first grade gauge block is within 1 μm, and the computing speed is doubled. When the algorithm is adopted to locate subpixel edge, the error caused by light source intensity can be effectively compensated through modifying the average of the Gauss integral model. Therefore, this algorithm can be applied to the high accurate measurement of mechanical parts, such as gears and etc.