Number of the records: 1

Pattern Recognition

SYSNO ASEP	0317725
Document Type	M - Monograph Chapter
R&D Document Type	Monograph Chapter
Title	Unsupervised Texture Segmentation
Title	Neřízená segmentace textur
Author(s)	Haindl, Michal (UTIA-B)_{RID, ORCID} Mikeš, Stanislav (UTIA-B)_RID
Source Title	Pattern Recognition, Unsupervised Texture Segmentation, chapter 9. - Vienna : In-Tech, 2008 / Yin Peng-Yeng - ISBN 978-953-7619-24-4
Pages	s. 227-248
Number of pages	22 s.
Number of copy	210
Number of pages	536
Publication form	www - www
Language	eng - English
Country	AT - Austria
Keywords	texture segmentation ; image segmentation ; unsupervised segmentation
Subject RIV	BD - Theory of Information
R&D Projects	1ET400750407 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
	GA102/08/0593 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
Annotation	Segmentation is the fundamental process which partitions a data space into meaningful salient regions. Image segmentation essentially affects the overall performance of any automated image analysis system thus its quality is of the utmost importance. Image regions, homogeneous with respect to some usually textural or colour measure, which result from a segmentation algorithm are analysed in subsequent interpretation steps. Several new unsupervised multispectral texture segmentation methods based on underlying Markovian spatial models with unknown number of classes are presented in the chapter. The performances of the presented methods are extensively tested on the Prague segmentation benchmark using the commonest segmentation criteria and compares favourably with several alternative texture segmentation methods.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2009

Number of the records: 1