Weighted Two-dimensional Otsu Threshold Approached for Image Segmentation

Abstract

According to the shortcomings of the traditional two-dimensional Otsu threshold method in segmentation accuracy and anti-production performance, an improved method based on weighted two-dimensional Otsu threshold segmentation image is proposed. On the basis of the cross-division of two-dimensional histogram, the distribution information of gray level and probability of gray value is used to comprehensively consider the influence of inter-class variance and intra-class variance on image segmentation, and the threshold value is weighted by the ratio of target and background in the image, which makes the threshold value closer to the ideal segmentation threshold. Finally, the simulation experiment is carried out to verify that the improved weighted segmentation method can achieve a good image segmentation effect and have better anti-noise ability.