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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/28093
Title: Selection texture regions on the image based on classification assessment density of contour elements
Authors: Alzakki, H. M.
Tsviatkou, V. Yu.
Альзаки, Х. М.
Цветков, В. Ю.
Keywords: материалы конференций
selection texture regions
contour elements
classification assessment density
Issue Date: 2017
Publisher: БГУИР
Citation: Alzakki, H. M. Selection texture regions on the image based on classification assessment density of contour elements / H. M. Alzakki, V. Tsviatkou // BIG DATA and Advanced Analytics: collection of materials of the third international scientific and practical conference. (Minsk, Belarus, May 3 – 4, 2017) / editorial board : М. Batura [etc.]. – Minsk : BSUIR, 2017. – С. 113 - 118.
Abstract: A method for texture images segmentation based on selection texture regions on the image based on classification assessment density of contour elements. The goal of the method find the contouring of the image, determin- ing the position of contour elements in the image and classify it for different types(points, lines, and shapes) close the region which had same type of contour type into binary regions objects. The result will be representing in binary matrix.
URI: https://libeldoc.bsuir.by/handle/123456789/28093
Appears in Collections:BIG DATA and Advanced Analytics. Использование BIG DATA для оптимизации бизнеса и информационных технологий (2017)

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