Scene Text Detection Based On Hierarchical Multilayer Perceptron

摘要：

In this paper,a new scene text detection method based on hierarchical multilayer perceptron (MLP)is proposed. First,connected components (CCs)are segmented locally by text probability map.Then,a novelty hierarchical architecture consisting of two MLP classifiers in tandem is utilized to analysis the CCs.In this hierarchical setup,the first stage MLP classifier trained using unary property features.The second stage MLP classifier is trained for CCs pairs including both posterior probabilities estimated by first stage and relationship features. Finally,candidate text CCs are grouping into words. Experimental results evaluated on the public dataset show that our approach yields better performance compared with state-of-the-art methods.

作者: Gang.Zhou Yuehu.Liu Jianji.Wang

作者单位: Institute of AI and Robotics Xian Jiaotong University Xian,P.R.China

会议类型: 国际会议

会议名称: 第八届IEEE信息与自动化国际会议(ICIC 2011)

会议地点: 深圳

会议语种:英文

页码: 215-220

在线出版日期: 2011-06-06（万方平台首次上网日期，不代表论文的发表时间）