计算机与数字工程2017，Vol.45Issue(6)：1194-1199,6.DOI:10.3969/j.issn.1672-9722.2017.06.037
应用耦合对象相似度的阈值分割方法研究
Threshold Segmentation Algorithm Research Used on Coupled Object Similarity
摘要
Abstract
Since the Otsu method and most of its improved methods take between-class variance as the foundation of picking threshold and the great difference of image segmentation results for different histogram distribution images,a new threshold segmen?tation algorithm which based on coupled object similarity is proposed in this paper. Firstly,a model of coupled object similarity is in?troduced,which can take both the relationship of the various attributes of the objects itself and the relationship between the proper?ties into account,and can capture the relationships between the objects with high accuracy and low algorithm complexity. Secondly, between-class variance in the Otsu method is replaced by coupled object similarity to pick threshold,each class distinguished by the selected threshold is regarded as an object in the model of coupled object similarity,each class has two attributes,the probabili?ty of class and gray mean. Similarity between classes is calculated,and the optimal threshold value is obtained according to the mini?mum of similarity between classes. The experiments can prove that the proposed algorithm can measure the difference of classes at a higher accuracy and obtain better segmentation results.关键词
图像分割/类间方差/耦合对象相似度/类间相似度/最优阈值Key words
image segmentation/between-class variance/coupled object similarity/between-class similarity/optimal threshold分类
信息技术与安全科学引用本文复制引用
武玉坤..应用耦合对象相似度的阈值分割方法研究[J].计算机与数字工程,2017,45(6):1194-1199,6.基金项目
国家自然科学基金青年项目(编号:61602059) （编号:61602059）
全国教育信息技术规划课题(编号:126240629)资助. （编号:126240629）
