DocumentCode :
2022111
Title :
Binarization of Badly Illuminated Document Images through Shading Estimation and Compensation
Author :
Lu, Shijian ; Tan, Chew Lim
Author_Institution :
Nat. Univ. of Singapore, Singapore
Volume :
1
fYear :
2007
fDate :
23-26 Sept. 2007
Firstpage :
312
Lastpage :
316
Abstract :
This paper presents a document image binarization technique that segments text from badly illuminated document images. Based on the observations that text documents normally lie over a planar or smoothly curved surface and have a uniformly colored background, badly illuminated document images are binarized by using a smoothing polynomial surface, which estimates the shading variation and compensates the shading degradation based on the estimated shading variation. Badly illuminated document images are accordingly binarized through the global thresholding of the compensated document images. Compared with the reported methods, the proposed technique is tolerant to the variations in text size and document contrast. At the same time, it is much faster and able to produce a binary text image with little background noise.
Keywords :
document image processing; image segmentation; polynomials; surface fitting; text analysis; background noise; badly illuminated document image binarization; binary text image; image segmentation; image thresholding; polynomial surface smoothing process; shading degradation compensation; shading variation estimation; Background noise; Degradation; Digital cameras; Image segmentation; Optical character recognition software; Pixel; Polynomials; Smoothing methods; Surface fitting; Text analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location :
Parana
ISSN :
1520-5363
Print_ISBN :
978-0-7695-2822-9
Type :
conf
DOI :
10.1109/ICDAR.2007.4378723
Filename :
4378723
Link To Document :
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