Mineral belt image segmentation of shaking table based on Genetic algorithm

At present, segmentation and identification of shaking table´s mineral belt image is artificial, which has the shortcomings of the lower accuracy and real-time. In order to overcome the defects and achieve automation of shaking table operation, this paper proposes mineral belt segmentation method based on genetic algorithm (GA) and two-dimensional Otsu. Experiments results show that the genetic algorithm is better than two-dimensional Otsu method in terms of segmentation accuracy, segmentation time, and convergence speed, and the genetic algorithm can separate middles from mineral belt, so GA is a better method for mineral belt image segmentation.