Publikation
Adaptive Binarization of Unconstrained Hand-Held Camera-Captured Document Images
Syed Saqib Bukhari; Faisal Shafait; Thomas Breuel
In: Journal of Universal Computer Science (JUCS), Vol. 15, No. 18, Pages 3343-3363, Springer, 12/2009.
Zusammenfassung
Abstract: This paper presents a new adaptive binarization technique for degraded
hand-held camera-captured document images. The state-of-the-art locally adaptive binarization methods are sensitive to the values of free parameter. This problem is more
critical when binarizing degraded camera-captured document images because of distortions like non-uniform illumination, bad shading, blurring, smearing and low resolution.
We demonstrate in this paper that local binarization methods are not only sensitive
to the selection of free parameters values (either found manually or automatically),
but also sensitive to the constant free parameters values for all pixels of a document
image. Some range of values of free parameters are better for foreground regions and
some other range of values are better for background regions. For overcoming this problem, we present an adaptation of a state-of-the-art local binarization method such that
two different set of free parameters values are used for foreground and background
regions respectively. We present the use of ridges detection for rough estimation of
foreground regions in a document image. This information is then used to calculate appropriate threshold using different set of free parameters values for the foreground and
background regions respectively. The evaluation of the method using an OCR-based
measure and a pixel-based measure show that our method achieves better performance
as compared to state-of-the-art global and local binarization methods.