Hybrid Binarization Method for Historical Handwritten Documents

Abstract

Binarization of historical documents is a rather complex task that is being intensively studied by researchers all over the world. A large number of approaches, procedures, and binarization algorithms have been proposed, but methods that work equally well in all cases have not yet been proposed. The literature offers various criteria for assessing the quality of the binarization result. In the case of binarization of ancient handwritten texts, the criterion for the quality of the binarization algorithm is the degree of readability of the text using a visual method or technical means. One of the approaches proposed in the literature to improve the quality of the binarization result is pre-processing the original image using filtering methods, morphological analysis, spectral analysis, etc. This article proposes a hybrid binarization method, consisting of an arbitrary global or adaptive binarization algorithm and a special segmentation procedure for selecting segments of certain sizes. The proposed procedure makes it possible to identify objects of certain sizes in an image, in particular artifacts that exist in a binarized image. This work experimentally explores the possibility of improving the quality of a binary image by applying the proposed procedure.