Abstract: Based on the ant colony optimization (ACO), a new algorithm for digital image correlation method is proposed. The procedure simulates the way that the real ants find the shortest path from their nest to food source and back. Modifications are made to the ACO algorithm in order to reduce the number of iterations and improve the quality of solutions. The accuracy and efficiency of the new method are demonstrated via application to computer-simulated images and comparison with widely used Newton-Raphson method. The feasibility and validity of the algorithm are also verified through experimentally obtained speckle images. The experimental results demonstrate the performance of our new algorithm.