计算机工程与应用2012，Vol.48Issue(28)：187-192,239,7.DOI:10.3778/j.issn.1002-8331.2012.28.039
基于最小风险贝叶斯分类器的茶叶茶梗分类
Classification of tea and stalk based on minimum risk Bayesian classifier
摘要
Abstract
Currently, in the process of actual production and processing of tea, the technology of tea-leaf and tea-stalk automational sorting is still in their infancy, and the precision and efficiency of sorting machinery hardly can achieve the desired objective. So the time and manpower costs must be increased again through the prcocess of manual sorting. In this paper, the digital camera is used to collect numeric pictures of tea-leaf and tea-stalk, then the color and shape features of these samples are extracted after pretreatment, and model is built with the use of multi-Gaussian model. The minimum risk Bayes classifier model is used to separate tea-leaf from tea-stalk. Experiments show that the minimum risk-based Bayesian classifier is feasible, and can obtain good classification results.关键词
最小风险/贝叶斯决策/数学形态学Key words
minimum risk/ Bayes decision/ mathematical morphplogy分类
信息技术与安全科学引用本文复制引用
张春燕,陈笋,张俊峰,李潭..基于最小风险贝叶斯分类器的茶叶茶梗分类[J].计算机工程与应用,2012,48(28):187-192,239,7.基金项目
国家自然科学基金(No.61073116/F020508). （No.61073116/F020508）
