In this paper, we present a contrast independent algorithm for binarization of degraded document images. The proposed algorithm does not require any parameter setting by user. Therefore, it can handle document images with variable foreground and background intensities a
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In this paper, we present a contrast independent algorithm for binarization of degraded document images. The proposed algorithm does not require any parameter setting by user. Therefore, it can handle document images with variable foreground and background intensities and low contrast documents. The proposed algorithm involves three consecutive stages. At the first stage, independent of contrast between foreground and background, sensible parts of each character are extracted using the modified water flow model, which is designed for the extraction of sensible part of each character and the drawbacks of water flow model are solved in this algorithm. In the second stage, the gray levels of foreground are estimated using the extracted text pixels and the gray levels of background are locally estimated by averaging the original image. At the third stage, for each pixel of image, the average of estimated foreground and background gray levels is defined as local threshold. After extensive experiments, the proposed binarization algorithm demonstrates superior performance against conventional binarization algorithms on a set of degraded document images captured with camera. Proposed algorithm efficiently extracts the low contrast texts.
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