基于贝叶斯网络的在线草图识别算法  

Online Sketch Recognition Algorithm Based on Bayesian Network

作　　者：袁贞明[1] 金贵朝[1] 张佳[1] 

机构地区：[1]杭州师范大学信息科学与工程学院,杭州310036

出　　处：《计算机工程》2010年第5期32-34,共3页Computer Engineering

基　　金：国家自然科学基金资助项目"智能视频监控中人脸图像的多尺度感知与理解"(60773051);浙江省自然基金资助项目"基于笔式人机交互的图形检索关键技术研究"(Y107631);浙江省科技计划基金资助项目"智能视频监控技术的研究与开发"(8C23033)

摘　　要：针对手绘草图识别算法大多采用限制用户绘制习惯来实现笔画分组的问题,提出一种基于贝叶斯网络的手绘草图识别算法。该算法将手绘草图识别中的笔画分组和符号识别统一为一个过程,用贝叶斯网络拓扑结构来表达草图结构信息。基于该网络,根据最大后验概率对连续输入的笔画进行动态最优分组,同时在线预测每组笔画的符号类别。实验结果表明,该方法是一种有效的在线递进式笔画分组和识别算法,在电路符号手绘识别中达到71.3%的过程识别率和85%的最终识别率。To solve the limitation of restricting the user＇s drawing style during the sketch grouping and recognition, a Bayesian network based sketch recognition algorithm is proposed, The algorithm combines the sketch grouping and the graphic symbol recognition into a unified procedure, which represents the sketch structure information as a Bayesian network. Based on the network, the growing sketches are grouped according to the maximum posterior probability, and each sketch group is recognized as a predefined symbol simultaneously. Experimental results show the effectiveness for the progressive sketch grouping and recognition, which has 71.3% procedure recognition rate and 85% final recognition rate.

关 键 词：贝叶斯网络 在线草图识别 笔画分组 符号识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]