Locally adaptive block thresholding method with continuity constraint
Pattern Recognition Letters
Document image binarization using wavelets for OCR applications
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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Abstract: Binarization of document images with poor contrast, strong noise complex patterns and variable modalities in the gray-scale histograms is a challenging problem. In this paper we present a binarization algorithm based on image dependent model to address this problem for the cheque processing application. The proposed algorithm seeks an optimal threshold that would eliminate the background noise, while preserving as much character stroke data as possible. The strategy is based on the use of information extracted from one clean part of the image, referred to as the "model" sub-image, to optimize the binarization in another problematic part of the image, referred to as the "target" sub-image. Experiments with 4,200 cheque images, provided by our industrial partner, showed significant improvement in the binarization quality in comparison with other well-established algorithms.