Efficient implementation of local adaptive thresholding techniques using integral images

Faisal Shafait; Daniel Keysers; Thomas M. Breuel

doi:10.1117/12.767755

28 January 2008 Efficient implementation of local adaptive thresholding techniques using integral images

Faisal Shafait, Daniel Keysers, Thomas M. Breuel

Proceedings Volume 6815, Document Recognition and Retrieval XV; 681510 (2008) https://doi.org/10.1117/12.767755
Event: Electronic Imaging, 2008, San Jose, California, United States

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.

Citation Download 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 (28 January 2008); https://doi.org/10.1117/12.767755

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