Improved Document Image Segmentation Algorithm using Multiresolution Morphology

被引：14
|
作者：
Bukhari, Syed Saqib [1 ]
Shafait, Faisal [2 ]
Breuel, Thomas M. [1 ]
机构：
[1] Tech Univ Kaiserslautern, Kaiserslautern, Germany
[2] German Res Ctr Artificial Intelligence DFKI, Kaiserslautern, Germany
来源：
DOCUMENT RECOGNITION AND RETRIEVAL XVIII | 2011年 / 7874卷
关键词：
Page Segmentation; Text/Non-Text Segmentation; Multiresolution Morphology;
D O I：
10.1117/12.873461
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,(1) which is also available in his open-source Leptonica library. 2 The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.
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页数：8
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