Degraded Chinese rubbing images thresholding based on local first-order statistics

Fang Wang; Ling-Ying Hou; Han Huang

doi:10.1117/12.2280301

19 June 2017 Degraded Chinese rubbing images thresholding based on local first-order statistics

Fang Wang, Ling-Ying Hou, Han Huang

Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 1044307 (2017) https://doi.org/10.1117/12.2280301
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore

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.

Citation Download Citation

Fang Wang, Ling-Ying Hou, and Han Huang "Degraded Chinese rubbing images thresholding based on local first-order statistics", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 1044307 (19 June 2017); https://doi.org/10.1117/12.2280301

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