BERILGAN TASVIR SIFATINI BAHOLASH
Abstract
In the development of systems for the analysis of handwritten text images, it is necessary to evaluate the quality of the given image. Usually, image quality assessment is done through its histogram, and it can be expressed accurately enough, but quality indicators cannot be expressed in quantitative values through this method. The task of quantitative assessment of image quality is a very complex and complex task, which undoubtedly allows for the correct strategy of image preprocessing algorithms. This provides a relatively high-quality image for analysis at the output.
References
Гонсалес Р., Вудс Р. Цифровая обработка изображений. – М.: Техносфера, 2012. – 1104 с.
Местецкий Л. М. Непрерывная морфология бинарных изображений. Фигуры. Скелеты. Циркуляры. – М.: Физматлит, 2009. – 287 с.
Шапиро Л., Стокман Дж. Компьютерное зрение. – М.: Бином. Лаборатория знаний, 2006. – 752 с.
Яне Б. Цифровая обработка изображений. – М.: Техносфера, 2007. – 583 с.
Al Maadeed S., Ayouby W., Hassaine A., Aljaam J.M. QUWI: An Arabic and English handwriting dataset for offline writer identification. In Proc. of Int. Conf. on Frontiers in Handwriting Recognition, 2012, pp. 746-751.
Mittal A., Moorthy A.K., and Bovik A.C. No-Reference Image Quality Assessment in the Spatial Domain. IEEE Transactions on Image Processing. Vol. 21, Number 12, December 2012, pp. 4695-4708.
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