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

被引：0

作者：

Wang, Fang ^{[1
]}

Hou, Ling-Ying ^{[1
]}

Huang, Han ^{[2
]}

机构：

[1] Nanchang Inst Technol, Coll Mech & Elect Engn, Nanchang 330099, Jiangxi, Peoples R China

[2] Northeastern Univ, Grad Sch Engn, 360 Huntington Ave, Boston, MA 02115 USA

来源：

SECOND INTERNATIONAL WORKSHOP ON PATTERN RECOGNITION | 2017年 / 10443卷

基金：

中国国家自然科学基金;

关键词：

Chinese rubbing image; Statistics; PHIBD; 2012; Binary; Image Segmentation; ALGORITHM;

D O I：

10.1117/12.2280301

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页数：6

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