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
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;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.216