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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/158559
Title: Reversible image merging for low-level machine vision
Authors: Kharinov, M.
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: In this paper a hierarchical model for pixel clustering and image segmentation is developed. In the model an image is hierarchically structured. The original image is treated as a set of nested images, which are capable to reversibly merge with each other. An object is defined as a structural element of an image, so that, an image is regarded as a maximal object. The simulating of none-hierarchical optimal pixel clustering by hierarchical clustering is studied. To generate a hierarchy of optimized piecewise constant image approximations, estimated by the standard deviation of approximation from the image, the conversion of any hierarchy of approximations into the hierarchy described in relation to the number of intensity levels by convex sequence of total squared errors is proposed.
URI: http://elib.bsu.by/handle/123456789/158559
Appears in Collections:2016. PATTERN RECOGNITION AND INFORMATION PROCESSING (PRIP’2016)

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