Optimization design of genetic algorithm in particle image velocimetry

Based on the modified genetic algorithm (GA), an improved disparity extraction method for three-dimensional (3-D) particle image velocimetry (PIV) is presented in this paper. Disparity is aligned to 1-D data array and encoded. The matching method, such as the sum of square difference (SSD) method and the sum of absolute difference (SAD) method, is employed to evaluate the results. Firstly, the crossover and mutation methods are used not only in chromosome but also inside every gene of a chromsome. Secondly, in order to reduce errors, the uniqueness is detected based on iterative algorithm. At last, synthetic particle images are tested and the results are analyzed. The experimental results show that the proposed method is suitable for stereo matching of 3-D particle images.