In photogrammetry, an approach of automatic detection and recognition on reference points have been proposed to meet the requirements on detection and matching of reference points. The reference points used here are the CCT(circular coded target), which compose of two parts: the round target point in central region and the circular encoding band in surrounding region. Firstly, the contours of image are extracted, after that noises and disturbances of the image are filtered out by means of a series of criteria, such as the area of the contours, the correlation coefficient between two regions of contours etc. Secondly, the cubic spline interpolation is adopted to process the central contour region of the CCT. The contours of the interpolated image are extracted again, then the least square ellipse fitting is performed to calculate the center coordinates of the CCT. Finally, the encoded value is obtained by the angle information from the circular encoding band of the CCT. From the experiment results, the location precision of the CCT can be achieved to sub-pixel level of the algorithm presented. Meanwhile the recognition accuracy is pretty high, even if the background of the image is complex and full of disturbances. In addition, the property of the algorithm is robust. Furthermore, the runtime of the algorithm is fast.