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Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

SYSNO ASEP	0327903
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation
Title	Hierarchický násobný markovský řetězový model pro neřízenou texturní segmentaci
Author(s)	Scarpa, G. (IT) Gaetano, R. (IT) Haindl, Michal (UTIA-B)_{RID, ORCID} Zerubia, J. (FR)
Source Title	IEEE Transactions on Image Processing. - : Institute of Electrical and Electronics Engineers - ISSN 1057-7149 Roč. 18, č. 8 (2009), s. 1830-1843
Number of pages	14 s.
Publication form	www - www
Language	eng - English
Country	US - United States
Keywords	Classification ; texture analysis ; segmentation ; hierarchical image models ; Markov process
Subject RIV	BD - Theory of Information
R&D Projects	GA102/08/0593 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
UT WOS	000268033300012
DOI	10.1109/TIP.2009.2020534
Annotation	In this paper, we present a novel multiscale texture model and a related algorithm for the unsupervised segmentation of color images. Elementary textures are characterized by their spatial interactions with neighboring regions along selected directions. Such interactions are modeled, in turn, by means of a set of Markov chains, one for each direction, whose parameters are collected in a feature vector that synthetically describes the texture. Based on the feature vectors, the texture are then recursively merged, giving rise to larger and more complex textures, which appear at different scales of observation: accordingly, the model is named Hierarchical Multiple Markov Chain (H-MMC). The Texture Fragmentation and Reconstruction (TFR) algorithm, addresses the unsupervised segmentation problem based on the H-MMC model.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2010

Number of the records: 1