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Please use this identifier to cite or link to this item: http://elib.bsu.by/handle/123456789/158762
Title: Generalized gradient: basic principles and example application
Authors: Kovalev, V.
Snezhko, E.
Kharuzhyk, S.
Liauchuk, V.
Keywords: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Информатика
ЭБ БГУ::ТЕХНИЧЕСКИЕ И ПРИКЛАДНЫЕ НАУКИ. ОТРАСЛИ ЭКОНОМИКИ::Медицина и здравоохранение
Issue Date: 2016
Publisher: Minsk: Publishing Center of BSU
Abstract: This paper presents a generalized approach for computing image gradient. It is predominantly aimed at detecting unclear and in certain circumstances even completely invisible borders in large 2D and 3D texture images. The method exploits the conventional approach of sliding window. Once two pixel/voxel sets are subsampled from orthogonal window halves, they are compared by a suitable technique (e.g., statistical t-test, SVM classifier, comparison of parameters of two distributions) and the resultant measure of difference (e.g., t-value, the classification accuracy, skewness difference of two distributions etc.) is treated as the gradient magnitude. The bootstrap procedure is employed for increasing the accuracy of difference assessment of two pixel/voxel sets.
URI: http://elib.bsu.by/handle/123456789/158762
Appears in Collections:2016. PATTERN RECOGNITION AND INFORMATION PROCESSING (PRIP’2016)

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