An evaluation of HMM-based Techniques for the Recognition of Screen Rendered Text

摘要：

Segmentation and recognition of screen rendered text is a challenging task due to its low resolution (72 or 96 ppi) and use of anti-aliased rendering. This paper evaluates Hidden Markov Model (HMM) techniques for OCR of low resolution text-both on screen rendered isolated characters and screen rendered text-lines-and compares it with the performance of other commercial and open source OCR systems. Results show that HMM-based methods reach the performance of other methods on screen rendered text and yield above 98% character level accuracies on both screen rendered text-lines and characters.

作者: Sheikh Faisal Rashid Faisal Shafait Thomas M.Breuel

作者单位: Technical University of Kaiserslautern, Kaiserslautern, Germany German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

会议类型: 国际会议

会议名称: 第11届文档分析与识别国际会议(ICDAR)

会议地点: 北京

会议语种:英文

页码: 1260-1264

在线出版日期: 2011-09-01（万方平台首次上网日期，不代表论文的发表时间）