Document image binarization result of manuscript "Binarization of Unevenly Illuminated Document Images Based on Cloth Simulation Filter"

Document image binarization is a crucial step in OCR algorithms. A binarization method that is robust to unevenly illuminated document images can provide better inputs for algorithms to recognize text under complex lighting conditions. By considering document images with uneven illumination as a terrain point cloud in 3D space, we transformed the problem of handling an uneven lighting background into a problem of ground filtering in the field of point cloud processing. We propose a binarization method based on the cloth simulation filter (CSF), a point cloud processing method, for binarizing unevenly illuminated document images. This dataset contains binarization results in the manuscript "Binarization of Unevenly Illuminated Document Images Based on Cloth Simulation Filter". The comparing methods include Adaptive, Bataineh, CSF(proposed), ISauvola, Sauvola, Su, TRSingh, and Wolf. All were applied with 176 images from the WEZUT dataset.