Отрывок: 30 87.57 “Spots and shadows” 69.82 73.91 “Complex” 80.56 84.10 “Simple” 98.38 98.59 The maximum accuracy for the global threshold bina- rization methods for the entire set is 93.76. This value is a result of the optimal thresholds (for each image from the dataset) set via manual segmentation. It surpasses the bal- anced Otsu by 9.46, and the unbalanced by 6.19 percent points. Thus, for the test data, replacement of the bal- anced criterion with the unbalanced o...
Полная запись метаданных
Поле DC | Значение | Язык |
---|---|---|
dc.contributor.author | Ershov, E.I. | - |
dc.contributor.author | Korchagin, S.A. | - |
dc.contributor.author | Kokhan, V.V. | - |
dc.contributor.author | Bezmaternykh, P.V. | - |
dc.date.accessioned | 2021-03-01 10:20:00 | - |
dc.date.available | 2021-03-01 10:20:00 | - |
dc.date.issued | 2021-02 | - |
dc.identifier | Dspace\SGAU\20210228\87754 | ru |
dc.identifier.citation | Ershov EI, Korchagin SA, Kokhan VV, Bezmaternykh PV. A generalization of Otsu method for linear separation of two unbalanced classes in document image binarization. Computer Optics 2021; 45(1): 66-76. DOI: 10.18287/2412-6179-CO-752. | ru |
dc.identifier.uri | https://dx.doi.org/10.18287/2412-6179-CO-752 | - |
dc.identifier.uri | http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/A-generalization-of-Otsu-method-for-linear-separation-of-two-unbalanced-classes-in-document-image-binarization-87754 | - |
dc.description.abstract | 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 Otsu method is not met. In this work, we considered the imbalanced pixel classes of background and text: 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 search via fast linear clustering was proposed. We also demonstrated that the two-parametric model with the proposed separation allows increasing the image binarization accuracy for the documents with a complex background or spots. | ru |
dc.description.sponsorship | We are grateful for the insightful comments offered by D.P. Nikolaev. This research was partially supported by the Russian Foundation for Basic Research No. 19-29-09066 and 18-07-01387. | ru |
dc.language.iso | en | ru |
dc.publisher | Самарский национальный исследовательский университет | ru |
dc.relation.ispartofseries | 45;1 | - |
dc.subject | threshold binarization | ru |
dc.subject | Otsu method | ru |
dc.subject | optimal linear classification | ru |
dc.subject | historical document image binarization | ru |
dc.title | A generalization of Otsu method for linear separation of two unbalanced classes in document image binarization | ru |
dc.type | Article | ru |
dc.textpart | 30 87.57 “Spots and shadows” 69.82 73.91 “Complex” 80.56 84.10 “Simple” 98.38 98.59 The maximum accuracy for the global threshold bina- rization methods for the entire set is 93.76. This value is a result of the optimal thresholds (for each image from the dataset) set via manual segmentation. It surpasses the bal- anced Otsu by 9.46, and the unbalanced by 6.19 percent points. Thus, for the test data, replacement of the bal- anced criterion with the unbalanced o... | - |
Располагается в коллекциях: | Журнал "Компьютерная оптика" |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
---|---|---|---|---|
450109.pdf | Основная статья | 3.28 MB | Adobe PDF | Просмотреть/Открыть |
Показать базовое описание ресурса
Просмотр статистики
Поделиться:
Все ресурсы в архиве электронных ресурсов защищены авторским правом, все права сохранены.