DocumentCode
2483250
Title
Natural Material Recognition with Illumination Invariant Textural Features
Author
Vácha, Pavel ; Haindl, Michal
Author_Institution
Inst. of Inf. Theor. & Autom., ASCR, Prague, Czech Republic
fYear
2010
fDate
23-26 Aug. 2010
Firstpage
858
Lastpage
861
Abstract
A visual appearance of natural materials fundamentally depends on illumination conditions, which significantly complicates a real scene analysis. We propose textural features based on fast Markovian statistics, which are simultaneously invariant to illumination colour and robust to illumination direction. No knowledge of illumination conditions is required and a recognition is possible from a single training image per material. Material recognition is tested on the currently most realistic visual representation-Bidirectional Texture Function (BTF), using the Amsterdam Library of Textures (ALOT), which contains 250 natural materials acquired in different illumination conditions. Our proposed features significantly outperform several leading alternatives including Local Binary Patterns (LBP, LBP-HF) and Gabor features.
Keywords
Markov processes; image colour analysis; image texture; bidirectional texture function; fast Markovian statistics; illumination colour; illumination conditions; illumination direction; illumination invariant textural features; natural material recognition; scene analysis; visual representation; Computational modeling; Image color analysis; Lighting; Materials; Pattern recognition; Pixel; Training; Markov random field; colour; illumination invariance; texture;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location
Istanbul
ISSN
1051-4651
Print_ISBN
978-1-4244-7542-1
Type
conf
DOI
10.1109/ICPR.2010.216
Filename
5596064
Link To Document