A generalization of otsu method for linear separation of two unbalanced classes in document image binarization

Авторы: Ershov E.I., Korchagin S.A., Kokhan V.V., Bezmaternykh P.V.
Журнал: Computer Optics
Том: 45
Номер: 1
Год издания: 2021
Первая страница: 66
Последняя страница: 76
DOI: 10.18287/2412-6179-CO-752
Аннотация: 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.
Добавил в систему: Корчагин Сергей Андреевич

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