A novel method for binarization of badly illuminated document images

This paper presents a novel document image binarization technique that separates text from background in badly illuminated document images. This technique is based on background estimation by using morphological closing operation. Binarization methods can be categorized into two categories: the global methods which do not work well in badly illuminated images, and the local methods which are usually parametric. In this paper a new local method is proposed. The most important feature of this local method is that, contrary to other common local methods, it is not dependent on any parameter. In other words it is an automatic method. Morphological closing operation is used to compensate for uneven background illumination. Closing operation is applied to remove small dark details while living the overall gray and larger dark features relatively undisturbed. Experiment results show that the proposed method offers better result for document images with bad degradation and lighting variance in comparison to former common methods.