摘要
最小最大概率机是基于错分概率最小化的新型分类器.文中讨论一维空间两类别最小最大概率问题的求解.以此为基础,给出图像阈值分割最小最大概率分割点的定义,提出设计阈值分割准则函数的方法,同时提出基于最小最大概率准则的阈值分割算法,此算法保证图像阈值分割正确率的下界.实验表明,文中方法是有效的.
The minimax probabilistic machine is a classifier based on minimizing the misclassification probability.The problem of 1-dimensional minimax probability machine is firstly discussed.Then a theory on minimax probabilistic image segmentation is presented.A method for developing criterion function for image thresholding is proposed.Meanwhile,the minimax probabilistic image thresholding algorithm is also proposed and it ensures the maximal lower bound for correctly classifying pixels.Experimental results show the effectiveness of the proposed algorithm.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2010年第6期880-884,共5页
Pattern Recognition and Artificial Intelligence
基金
国家863计划项目(No.2007AA1Z158)
国家自然科学基金项目(No.60704047
60903100)资助
关键词
图像阈值分割
最小最大概率
非参数法
Image Thresholding
Minimax Probability
Non-Parametric Method
