关键词: 全局阈值分割, 遗传算法, 大津算法

Abstract: For some field images, it is difficult to determine the optimal threshold problem of image segmentation due to its complicated background and uneven illumination. This paper proposes an image segmentation method based on improved Otsu algorithm optimization and improved genetic algorithm. Firstly, the acquired images are pre-processed. Based on the preprocessed images, the genetic control parameters can be automatically adjusted by improving the three methods of selection, crossover and variation in the genetic algorithm and optimizing the individual fitness function based on Otsu, so as to ensure the diversity of species and accelerate its convergence speed. The optimal threshold is provided for the Otsu image segmentation, and finally the image is filled by image morphology. In the result of the discussion, the algorithm results are compared with the Genetic Algorithm Based on the Otsu Algorithm and the Image Segmentation Based on Genetic Algorithm and KSW Entropy. It is found that the threshold range obtained by the algorithm is stable, which makes the segmented image accurate and clear. It is helpful to calculate the number of crops or the coverage of plants in the later stage.

Key words: global threshold segmentation, genetic algorithm, Otsu algorithm