Soil image segmentation based on fuzzy clustering OTSU

Guochao Shen; Jiaojie Li; Quchao Cheng

doi:10.1117/12.2611687

22 October 2021 Soil image segmentation based on fuzzy clustering OTSU

Guochao Shen, Jiaojie Li, Quchao Cheng

Proceedings Volume 11928, International Conference on Image Processing and Intelligent Control (IPIC 2021); 119280U (2021) https://doi.org/10.1117/12.2611687
Event: International Conference on Image Processing and Intelligent Control (IPIC 2021), 2021, Lanzhou, China

Abstract

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.

Citation Download Citation

Guochao Shen, Jiaojie Li, and Quchao Cheng "Soil image segmentation based on fuzzy clustering OTSU", Proc. SPIE 11928, International Conference on Image Processing and Intelligent Control (IPIC 2021), 119280U (22 October 2021); https://doi.org/10.1117/12.2611687

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