MSWOA: A Mixed-Strategy-Based Improved Whale Optimization Algorithm for Multilevel Thresholding Image Segmentation

Multilevel thresholding image segmentation is one of the most widely used methods in field segmentation. This paper proposes a multilevel technique based on an improved whale optimization algorithm. The WOA has been applied to many complex problems because its excellent performance; however, it easily falls into local optimization. Therefore, firstly, mixed-strategy-based algorithm (MSWOA) proposed using k-point initialization algorithm, nonlinear convergence factor, and adaptive weight coefficient improve ability Then, MSWOA combined with Otsu method Kapur entropy search for optimal thresholds gray segmentation, respectively. results performance evaluation experiments benchmark functions demonstrate that higher accuracy faster speed than other comparative algorithms can effectively jump out optimum. In addition, experimental images show MSWOA–Kapur accurately thresholds.