A Fuzzy Thresholding Segmentation for Plant Root CT Images Based on Genetic Algorithm
基于遗传算法的原位根系CT图像的模糊阈值分割

The CT images segmentation is one of key technologies for the 3D reconstruction and quantitative analysis of plant root system in situ. In order to improve the precision and efficiency of images segmentation,in accordance with the inherent indistinction of CT images, a fuzzy thresholding algorithm was implemented with the criterion of maximum fuzzy entropy and genetic algorithm. The initial thresholds were obtained with histogram analysis. The CT images were divided into several different regions fuzzily through designing a simple fuzzy neighborhood function. And according to the criterion of maximum fuzzy entropy, a genetic algorithm was used to find out the best thresholds of CT images segmentation. The result of programming test shows that the algorithm is effective to improve the precision and efficiency of root CT images segmentation.