Soil image segmentation based on fuzzy clustering OTSU

The composition of the soil is very important, therefore, it is necessary to separate soil and other components from soil images in order to facilitate the study of soil components. This paper mainly studies the realization method of soil image segmentation, especially the traditional maximal inter-class variance method in global threshold method. On this basis, the fuzzy C-means clustering algorithm is combined with fuzzy theory to optimize the algorithm. By comparing the experimental results, it is proved that the fuzzy C-means clustering algorithm based on the maximum inter-class segmentation method can achieve the segmentation of objects and backgrounds, and meet the requirements of image segmentation.