Abstract: In order to improve the performance of integer-pixel displacement search algorithm of digital image correlation(DIC) method, the white shark optimizer was introduced and improved by adopting tent mapping, introducing dynamic nonlinear time factor, setting automatic termination condition and adding three-step search method. In order to improve the accuracy and efficiency of sub-pixel displacement solving, an improved surface fitting method was proposed by combining bicubic interpolation, and the white shark optimizer and surface fitting method was improved. The performance of the two algorithms was tested by numerical simulation experiments and tensile experiment of low-carbon steel. The experimental results exposes that, the improved white shark optimizer has a search success rate of up to 100%, with a computational time comparable to that of the particle swarm optimization and only a quarter of that of the coarse-fine search method. The computational accuracy of the improved surface fitting method is comparable to that of the Newton-Raphson(N-R)algorithm, but the computational time consumed is only 3.50% of the N-R algorithm. The improved white shark optimizer can achieve integer-pixel displacement search quickly and accurately. The improved surface fitting method has high computational accuracy and efficiency, and still maintains good stability in actual measurements. This study provides a reference for the improvement and application of digital image correlation method.