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Aiming at the traditional production of safety buckles that cannot achieve clamping when there is a deviation in position placement, a method for rapid identification and positioning of disordered safety buckles is proposed. The method adopts an improved NCC algorithm based on sub-templates and image pyramids for template matching, and combines with the circular projection algorithm to achieve the target detection of rotating safety buckles, and also adopts the cross-matching and RANSAC based methods for accurate positioning of safety buckles. The experimental validation is carried out by comparing the positioning results with the actual coordinates, and the results show that the recognition error is 0~1 pixel, in which the average error of the X-axis is only 1.02mm, while the average error of the Y-axis is 0.76mm, which achieves the accurate recognition and positioning of the disordered safety buckles, and is able to satisfy the practical needs in engineering.