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Proceedings Paper

Degraded Chinese rubbing images thresholding based on local first-order statistics
Author(s): Fang Wang; Ling-Ying Hou; Han Huang
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Paper Abstract

It is a necessary step for Chinese character segmentation from degraded document images in Optical Character Recognizer (OCR); however, it is challenging due to various kinds of noising in such an image. In this paper, we present three local first-order statistics method that had been adaptive thresholding for segmenting text and non-text of Chinese rubbing image. Both visual inspection and numerically investigate for the segmentation results of rubbing image had been obtained. In experiments, it obtained better results than classical techniques in the binarization of real Chinese rubbing image and PHIBD 2012 datasets.

Paper Details

Date Published: 19 June 2017
PDF: 6 pages
Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 1044307 (19 June 2017); doi: 10.1117/12.2280301
Show Author Affiliations
Fang Wang, Nanchang Institute of Technology (China)
Ling-Ying Hou, Nanchang Institute of Technology (China)
Han Huang, Northeastern Univ. (United States)

Published in SPIE Proceedings Vol. 10443:
Second International Workshop on Pattern Recognition
Xudong Jiang; Masayuki Arai; Guojian Chen, Editor(s)

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