Improved Document Image Segmentation Algorithm using Multiresolution Morphology
Identifieur interne : 000113 ( PascalFrancis/Checkpoint ); précédent : 000112; suivant : 000114Improved Document Image Segmentation Algorithm using Multiresolution Morphology
Auteurs : SYED SAQIB BUKHARI [Allemagne] ; Faisal Shafait [Allemagne] ; Thomas M. Breuel [Allemagne]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2011.
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Abstract
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,l 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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<front><div type="abstract" xml:lang="en">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,<sup>l</sup>
which is also available in his open-source Leptonica library.<sup>2</sup>
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.</div>
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