摘要
提出二维 Otsu 阈值法的快速迭代算法.针对传统二维 Otsu 阈值法及改进的递推二维 Otsu 阈值法等具有高计算复杂性的不足,假设被分割图像及其邻域平滑图像形成的二维联合直方图是连续二元概率分布函数的条件下,利用求多元函数极值的方法得到二维 Otsu 阈值法的快速迭代算法.大量实验结果表明,本文方法是可行的且有良好的分割性能.
A fast iterative algorithm for two-dimensional Otsu thresholding method is proposed. Considering the disadvantages of the classical two-dimensional Otsu thresholding method and its recursive algorithm, it is supposed that the two-dimensional histogram which is composed of original segmented image and its local neighborhood average image is a two-variable continuous probability distribution function. The method for seeking extreme value of multivariate function is employed and the fast iterated algorithm of two-dimensional Otsu thresholding method is obtained. The experimental results show that the proposed fast iterative algorithm is feasible and has better segmentation performance.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2008年第6期746-757,共12页
Pattern Recognition and Artificial Intelligence
基金
中国科学院自动化研究所模式识别国家重点实验室开放课题项目(No.07-31-3)
陕西省教育厅科学研究计划项目(No.06JK194)资助
关键词
图像分割
阈值法
OTSU法
递推算法
迭代算法
Image Segmentation, Thresholding Method, Otsu Method, Recursive Algorithm, Iterative Algorithm
