当前位置: X-MOL 学术Comput. Vis. Image Underst. › 论文详情
Text Extraction from Scene Images by Character Appearance and Structure Modeling.
Computer Vision and Image Understanding ( IF 2.645 ) Pub Date : 2013-01-15 , DOI: 10.1016/j.cviu.2012.11.002
Chucai Yi,Yingli Tian

In this paper, we propose a novel algorithm to detect text information from natural scene images. Scene text classification and detection are still open research topics. Our proposed algorithm is able to model both character appearance and structure to generate representative and discriminative text descriptors. The contributions of this paper include three aspects: 1) a new character appearance model by a structure correlation algorithm which extracts discriminative appearance features from detected interest points of character samples; 2) a new text descriptor based on structons and correlatons, which model character structure by structure differences among character samples and structure component co-occurrence; and 3) a new text region localization method by combining color decomposition, character contour refinement, and string line alignment to localize character candidates and refine detected text regions. We perform three groups of experiments to evaluate the effectiveness of our proposed algorithm, including text classification, text detection, and character identification. The evaluation results on benchmark datasets demonstrate that our algorithm achieves the state-of-the-art performance on scene text classification and detection, and significantly outperforms the existing algorithms for character identification.
更新日期:2019-11-01

 

全部期刊列表>>
化学/材料学中国作者研究精选
ACS材料视界
南京大学
自然科研论文编辑服务
剑桥大学-
中国科学院大学化学科学学院
南开大学化学院周其林
课题组网站
X-MOL
北京大学分子工程苏南研究院
华东师范大学分子机器及功能材料
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug