Efficient Implementation of Local Adaptive Thresholding Techniques Using Integral Images

Faisal Shafait, Daniel Keysers, Thomas Breuel
Proceedings of the 15th Document Recognition and Retrieval Conference (DRR-2008), Part of the IS&T/SPIE International Symposium on Electronic Imaging, January 26-31, San Jose, CA, USA volume 6815, SPIE, 1/2008
Accepted for publication


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.

Files:

  FsDkTmbEfficientImplSpie2008.pdf

BibTex:

@inproceedings{ SHAF2008,
	Title = {Efficient Implementation of Local Adaptive Thresholding Techniques Using Integral Images},
	Author = {Faisal Shafait and Daniel Keysers and Thomas Breuel},
	BookTitle = {Proceedings of the 15th Document Recognition and Retrieval Conference (DRR-2008), Part of the IS&T/SPIE International Symposium on Electronic Imaging, January 26-31, San Jose, CA, USA},
	Note = {Accepted for publication},
	Month = {1},
	Year = {2008},
	Publisher = {SPIE},
	Publisher = {6815}
}

     
Last modified:: 30.08.2016