In order to improve the accuracy and efficiency of solution of the subpixel displacement measurement of non-iterative gray-gradient algorithm in digital image correlation, an improved algorithm based on artificial neural network is proposed. The Back Propagation (BP) artificial neural network was employed to build directly the nonlinear mapping relationship between the gray and gray-gradient in the subimages of speckle images before and after deformation and subpixel displacements, without the need for least square analytical optimal solution of correleation coefficient. Speckle images were simulated and applied to verify the accuracy and efficiency of solution of the Subpixel displacement measurement of the algorithm. The results reveal that the proposed algorithm has higher computation accuracy and efficiency than traditional non-iterative gray-gradient algorithm. The validity of the proposed algorithm is verified further by rigid body translation experiment finally.