Institute of Information Theory and Automation

Publication details

Colour and rotation invariant textural features based on Markov random fields

Journal Article

Vácha Pavel, Haindl Michal, Suk Tomáš


serial: Pattern Recognition Letters vol.32, 6 (2011), p. 771-779

research: CEZ:AV0Z10750506

project(s): 1M0572, GA MŠk, GA102/08/0593, GA ČR, 2C06019, GA MŠk

keywords: Image modelling, colour texture, Illumination invariance, Markov random field, rotation invariance

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abstract (eng):

A visual appearance of natural materials significantly depends on acquisition circumstances, particularly illumination conditions and viewpoint position, whose variations cause difficulties in the analysis of real scenes. We address this issue with novel texture features, based on fast estimates of Markovian statistics, that are simultaneously rotation and illumination invariant. The proposed features are invariant to inplane material rotation and illumination spectrum (colour invariance), they are robust to local intensity changes (cast shadows) and illumination direction. No knowledge of illumination conditions is required and recognition is possible from a single training image per material. The material recognition is tested on the currently most realistic visual representation – Bidirectional Texture Function (BTF), using CUReT and ALOT texture datasets with more than 250 natural materials.

RIV: BD

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Last modification: 21.12.2012
Institute of Information Theory and Automation