Segmentation for path analysis based on OTSU and immune genetic algoritnm

In this paper, we firstly introduce the path analysis of tracking robot, and then introduce the advantages of immune genetic algorithm (IGA). Thirdly, we combine immune genetic algorithm and OTSU threshold method to segment path of tracking robot. Because of the nonlinear solving process of immune genetic algorithm, for each chromosome, the solution of fitness function is separated. And the genetic algorithm is independent of each other, which is suitable for parallel computing and satisfy real time requirements. So OTSU combined with immune genetic algorithm not only improve the segmentation performance, but also enhance the computing speed of the algorithm. At last, the experiment results demonstrate the effectiveness of the algorithm.