Text Detection in Natural Scene Images Leveraging Context Information

摘要：

　　In this paper,we propose a method leveraging context information for text detection in natural scene images.Most of the existing methods just utilize the hand-engineered features to describe the text area,but we focus on building a confidence map model by integrating the candidate appearance and the relationships with its adjacent candidates.Three layers of filtering strategy is designed to judge the category of the text candidates,which can remove abundant non-text regions.In order to retrieve the missing text regions,a context fusion step is performed.Finally,the remaining connected components (CCs) are grouped into text lines and are further verified,and then the text lines are broken into separate words.Experimental results on two benchmark datasets,i.e.,ICDAR 2005,ICDAR 2013,demonstrate that the proposed approach has achieved the competitive performances with the state-of-the-art algorithms.

关键词： Text detection context information confidence map natural scene image

作者: Runmin Wang Nong Sang Changxin Gao Xiaoqin Kuang Jun Xiang

作者单位: School of Automation,Huazhong University of Science and Technology,Wuhan,China,430074

会议类型: 国际会议

会议名称: Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)

会议地点: 长沙

会议语种:英文

页码: 444-454

在线出版日期: 2014-11-01（万方平台首次上网日期，不代表论文的发表时间）