Scene Text Detection Based on Text Probability and Pruning Algorithm

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• 关键词：Scene text detection ; Maximum stable extreme regions ; Text probability ; Pruning algorithm
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9773
• 期：1
• 页码：726-735
• 全文大小：1,863 KB
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• 作者单位：Gang Zhou (16)
  Yajun Liu (16)
  Fei Shi (16)
  Ying Hu (16)
  
  16. The Institution of Information Science and Technology, Xinjiang University, Shengli Road, 14, Ürümqi, 830001, China
  
• 丛书名：Intelligent Computing Methodologies
• ISBN：978-3-319-42297-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9773

文摘

As the scene text detection and localization is one of the most important steps in text information extraction system, it had been widely utilized in many computer vision tasks. In this paper, we introduce a new method based on the maximally stable extremal regions (MSERs). First, a coarse-to-fine classier estimates the text probability of the ERs. Then, a pruning algorithm is introduced to filter non-text MSERs. Secondly, a hybrid method is performed to cluster connected components (CCs) as candidate text strings. Finally, a fine design classifier decides the text strings. The experimental results show our method gets a state-of-the-art performance on the ICDAR2005 dataset.