Effective Binarization of Document Images with Uneven Shading
AbstractWith rapid popularization of mobile camera, capturing a document and storing it become easy. However, when the document is illuminated under poor conditions, the document image may appear uneven shading. In that case, it is difficult to restore texts for character recognition and document analysis etc. In this paper, we propose an effective and simple approach to remove uneven shading from a document image. First, a local uneven shading is estimated using a constant time weighted median filter. Then, reflectance is computed by removing the uneven shading based on retinex theory, followed by a bandpass thresholding to partially binarize the clean document image. Finally, the unbinarized pixels are classified into text and background by using contrast map weighted graphcut approach. A host of experimental results demonstrate that the proposed method runs effectively and has pleasurable performance.
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