ИСТИНА

The classical Otsu method is a common tool in document image binarization. Often, two classes, text and background, are imbalanced, which means that the assumption of the classical Otsumethod is not met. In this work, we considered the imbalanced pixel classes of background andtext: weights of two classes are different, but variances are the same. We experimentally demonstrated that the employment of a criterion that takes into account the imbalance of the classes’weights, allows attaining higher binarization accuracy. We described the generalization of the criteria for a two-parametric model, for which an algorithm for the optimal linear separation searchvia fast linear clustering was proposed. We also demonstrated that the two-parametric model withthe proposed separation allows increasing the image binarization accuracy for the documents witha complex background or spots.