基于贝叶斯网络的草图符号识别研究  

Research of Sketch Symbol Recognition Based on Bayesian Network

作　　者：李路[1] 周良[1] 丁秋林[1] 

机构地区：[1]南京航空航天大学信息科学与技术学院,南京210016

出　　处：《计算机科学》2011年第6期262-265,共4页Computer Science

摘　　要：针对草图识别算法大多通过限制用户绘制习惯来提高识别精确度的问题,提出一种动态构造贝叶斯网络模型的草图符号识别方法。该方法采用了从下而上与从上而下相结合的识别算法。从下而上实现笔画的分割,根据后验概率产生假设模板,继而产生图形模板。在从上而下的处理中,通过假设模板重构实现笔画重组、根据图形模板的空槽实现笔画识别的纠错处理。通过对UML领域中草图符号的识别,表明算法能在不限制用户绘制习惯的基础上取得较好的识别效果。To solve the current algorithm＇s limitation of restricting the users＇ drawing style,this article introduced a method of dynamically constructing Bayes net to sketch symbol recognition system.This paper adopted a identifying algorithm which is a combination of bottom-top and top-bottom.From bottom to top it realizes the segmentation of strokes,generating hypothesis templates according to posterior probability then generating graphics templates.From top to bottom it realizes regrouping strokes through reconfiguring hypothesis templates and handling nosiy input according to the empty slot of templates.Through being applied to the domain of UML,we can get better recognition effect without restricting users＇ freely input.

关 键 词：贝叶斯网络 先验概率 后验概率 符号识别 假设模板 

分 类 号：TP393.092[自动化与计算机技术—计算机应用技术]