Image segmentation is a basic and important issue in field of computer vision.Entropy threshold image segmentation,as an effective segmentation method,is widely used in pattern recognition and image processing.Traditional image segmentation methods cannot obtain enough effective image features.In order to solve this problem and further explore the application of entropy threshold in image segmentation,a GLLE (Gray Level and Local Entropy) two-dimensional histogram is introduced to improve the entropy threshold image segmentation model,and a method based on fuzzy entropy is proposed to calculate the established two-dimensional histogram model.The comparison experiments on standard experimental datasets show that the proposed GLLE entropy threshold segmentation method based on fuzzy entropy can get more accurate thresholds and improve the segmentation accuracy.Compared with traditional algorithms,our method performs better on different types of images,and has stronger robustness.