CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 5
Clicked: 6635
ZHANG Jun-song, YU Jin-hui, MAO Guo-hong, YE Xiu-zi. Denoising of Chinese calligraphy tablet images based on run-length statistics and structure characteristic of character strokes[J]. Journal of Zhejiang University Science A, 2006, 7(7): 1178-1186.
@article{title="Denoising of Chinese calligraphy tablet images based on run-length statistics and structure characteristic of character strokes",
author="ZHANG Jun-song, YU Jin-hui, MAO Guo-hong, YE Xiu-zi",
journal="Journal of Zhejiang University Science A",
volume="7",
number="7",
pages="1178-1186",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1178"
}
%0 Journal Article
%T Denoising of Chinese calligraphy tablet images based on run-length statistics and structure characteristic of character strokes
%A ZHANG Jun-song
%A YU Jin-hui
%A MAO Guo-hong
%A YE Xiu-zi
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 7
%P 1178-1186
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1178
TY - JOUR
T1 - Denoising of Chinese calligraphy tablet images based on run-length statistics and structure characteristic of character strokes
A1 - ZHANG Jun-song
A1 - YU Jin-hui
A1 - MAO Guo-hong
A1 - YE Xiu-zi
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 7
SP - 1178
EP - 1186
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A1178
Abstract: In this paper, a novel approach is proposed for denoising of Chinese calligraphy tablet documents. The method includes two phases: First, a partial differential equations (PDE) based the total variation model and Otsu thresholding method are used to preprocess the calligraphy document image. Second, a new method based on run-length statistics and structure characteristics of Chinese characters is proposed to remove some random and ant-like noises. This includes the optimal threshold selection from histogram of run-length probability density, and improved Hough transform algorithm for line shape noise detection and removal. Examples are given in the paper to demonstrate the proposed method.
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