Image Converting into Complex Networks : Scale- Level Segmentation Approach; Advances in Computer Science Research; Vol. 72 : Information technologies in Science, Management, Social sphere and Medicine (ITSMSSM 2017)

Image Converting into Complex Networks : Scale- Level Segmentation Approach; Advances in Computer Science Research; Vol. 72 : Information technologies in Science, Management, Social sphere and Medicine (ITSMSSM 2017)

Bibliographic Details
Parent link:	Advances in Computer Science Research Vol. 72 : Information technologies in Science, Management, Social sphere and Medicine (ITSMSSM 2017).— 2017.— [P. 417-422]
Corporate Author:	Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Other Authors:	Trufanov A. Andrey, Kinash N. Nikolay, Berestneva O. G. Olga Grigorievna, Tikhomirov A. Alexei, Rossodivita A. Alessandra
Summary:	Title screen Image analysis and recognition is being a contemporary domain for successful tries to apply complex networks as an instrument for thorough studies. Researchers noted that an image having traditionally converted into a network (i.e. taking into account Euclidean distance between pixels only) possesses nodes with similar number of admissible links and the concomitant graph demonstrates a regular topology. As a rule, pixel intensity difference is considered to escape regularity and reach complex property of the network. Contrary revealing more specific traits of an image current study proposes scale segmentation views -local, medium and global - for an image to build a genuine complex network. Case study with two sample images manifests how the scales are connected with formation of a network topology.
Language:	English
Published:	2017
Subjects:	электронный ресурс труды учёных ТПУ images complex networks conversion topology segmentation spatial scales изображения сложные сети преобразования топология интегральных микросхем сегментация пространственные масштабы
Online Access:	http://dx.doi.org/10.2991/itsmssm-17.2017.88
Format:	Electronic Book Chapter
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=657538

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