DocumentCode :
3142579
Title :
A robust skew detection algorithm for grayscale document image
Author :
Chen, Ming ; Ding, Xiaoqing
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
fYear :
1999
fDate :
20-22 Sep 1999
Firstpage :
617
Lastpage :
620
Abstract :
A fast and robust skew detection algorithm for gray-scale images is presented. The MCCSD (modified cross-correlation skew detection) algorithm uses horizontal and vertical cross-correlation simultaneously to deal with vertically laid-out text, which is commonly used in Chinese or Japanese documents. Instead of calculating the correlation for the entire image, we use small randomly selected regions to speed up the process. The region verification stage and further processing of auxiliary peaks make our method robust and reliable. An experiment shows that the proposed method has good results in detecting skew in various kinds of pages
Keywords :
correlation methods; document image processing; Chinese documents; Japanese documents; MCCSD algorithm; auxiliary peaks; grey-scale document images; horizontal cross-correlation; modified cross-correlation skew detection; randomly selected regions; region verification; robust page skew detection algorithm; vertical cross-correlation; vertical layout text; vertically laid-out text; Detection algorithms; Gray-scale; Image analysis; Image color analysis; Image segmentation; Nearest neighbor searches; Robustness; Sun; Text analysis; Text recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
Conference_Location :
Bangalore
Print_ISBN :
0-7695-0318-7
Type :
conf
DOI :
10.1109/ICDAR.1999.791863
Filename :
791863
Link To Document :
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