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Pattern Recognition, Recent Advances

SYSNO ASEP	0343263
Document Type	M - Monograph Chapter
R&D Document Type	Monograph Chapter
Title	Illumination Invariants Based on Markov Random Fields
Author(s)	Vácha, Pavel (UTIA-B)_RID Haindl, Michal (UTIA-B)_{RID, ORCID}
Source Title	Pattern Recognition, Recent Advances. - Vukovar, Croatia : In-Teh, 2010 / Herout A. - ISBN 978-953-7619-90-9
Pages	s. 253-272
Number of pages	20 s.
Number of copy	5000
Number of pages	524
Publication form	www - www
Language	eng - English
Country	HR - Croatia
Keywords	illumination invariants ; textural features ; Markov random fields
Subject RIV	BD - Theory of Information
R&D Projects	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	Content-based image retrieval systems (CBIR) typically query large image databases based on some automatically generated colour and textural features. Optimal robust features should be geometry and illumination invariant. Although image retrieval has been an active research area for many years this difficult problem is still far from being solved. We introduce fast and robust textural features that allow retrieving images with similar scenes comprising colour textured objects viewed with different illumination. The proposed textural features that are invariant to illumination spectrum and extremely robust to illumination direction. They require only a single training image per texture and no knowledge of illumination direction, brightness or spectrum. These feature utilises utilise illumination invariant features extracted from three different Markov random field (MRF) based texture representations.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2011

Number of the records: 1