This paper uses the ant colony optimization method to detect dominant points. It develops a dominant point detection system for closed target images with simple backgrounds. The process is to perform image preprocessing on the captured object images, then perform object contour tracking and breakpoint detection, and finally use the ant colony optimization method to detect the object's dominant points. In such problems, ant colony calculus is applied to such problems by first defining a fitness value. In addition, three different hybrid strategies, including the minimum error method, the maximum distance method, and the random selection method, were also experimentally compared. Experimental results show that the used hybrid strategy can improve the computational efficiency of all three types of problems.