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Proceedings Paper

Region-based document image denoising
Author(s): Qing-Wen Zhou; Kai Wang; Hong-Jiang You; Qing-Ren Wang
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Paper Abstract

Traditional image de-noising methods mainly focus on the global effect, but the noise in document images tends to gather in certain local areas. So global de-noising processes will inevitably affect the recognition rate. Region based image de-noising uses pixel statistical information of local regions to separate noise and non-noise regions. And de-noising only applies on these noise regions instead of the entire image. So the deficiency of traditional method can be overcome. Test result on UNLV with 11176 samples shows that the average recognition rate rises from 94.44% to 94.85% by using this method.

Paper Details

Date Published: 20 August 2010
PDF: 6 pages
Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78202G (20 August 2010); doi: 10.1117/12.866973
Show Author Affiliations
Qing-Wen Zhou, Nankai Univ. (China)
Kai Wang, Nankai Univ. (China)
Hong-Jiang You, Nankai Univ. (China)
Qing-Ren Wang, Nankai Univ. (China)


Published in SPIE Proceedings Vol. 7820:
International Conference on Image Processing and Pattern Recognition in Industrial Engineering
Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du, Editor(s)

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