An innovative document image binarization approach driven by the non-local p-Laplacian

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Abstract Text image binarization is fairly a tedious task and a significant problem in document image analysis. This process, as a necessary pretreatment for noisy images with stains, non-uniform background, or degraded text characters, can successfully improve the quality of the image and facilitate the subsequent image processing steps. A theoretically well-motivated non-local method for document image binarization is addressed in this paper. This approach enhances degraded images by estimating and then removing the undesirable background. Extensive experiments conducted on degraded document images evince the greater effectiveness of the proposed non-local algorithm.

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