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Proceedings Article

Efficient implementation of local adaptive thresholding techniques using integral images

[+] Author Affiliations
Faisal Shafait, Daniel Keysers

German Research Ctr. for Artificial Intelligence (Germany)

Thomas M. Breuel

Technical Univ. of Kaiserslautern (Germany)

Proc. SPIE 6815, Document Recognition and Retrieval XV, 681510 (January 28, 2008); doi:10.1117/12.767755
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From Conference Volume 6815

  • Document Recognition and Retrieval XV
  • Berrin A. Yanikoglu; Kathrin Berkner
  • San Jose, CA | January 27, 2008

abstract

Adaptive binarization is an important first step in many document analysis and OCR processes. This paper describes a fast adaptive binarization algorithm that yields the same quality of binarization as the Sauvola method,1 but runs in time close to that of global thresholding methods (like Otsu's method2), independent of the window size. The algorithm combines the statistical constraints of Sauvola's method with integral images.3 Testing on the UW-1 dataset demonstrates a 20-fold speedup compared to the original Sauvola algorithm.

© (2008) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Faisal Shafait ; Daniel Keysers and Thomas M. Breuel
"Efficient implementation of local adaptive thresholding techniques using integral images", Proc. SPIE 6815, Document Recognition and Retrieval XV, 681510 (January 28, 2008); doi:10.1117/12.767755; http://dx.doi.org/10.1117/12.767755


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