IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Features and Learning Similarity
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Image retrieval measures based on illumination invariant textural MRF features
Proceedings of the 6th ACM international conference on Image and video retrieval
Performance evaluation of local colour invariants
Computer Vision and Image Understanding
Material-specific adaptation of color invariant features
Pattern Recognition Letters
International Journal of Computer Vision
Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Dominant local binary patterns for texture classification
IEEE Transactions on Image Processing
Natural Material Recognition with Illumination Invariant Textural Features
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
CLUE: cluster-based retrieval of images by unsupervised learning
IEEE Transactions on Image Processing
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A content-based tile retrieval system based on the underlying multispectral Markov random field representation is introduced. Single tiles are represented by our approved textural features derived from especially efficient Markovian statistics and supplemented with Local Binary Patterns (LBP) features representing occasional tile inhomogeneities. Markovian features are on top of that also invariant to illumination colour and robust to illumination direction variations, therefore an arbitrary illuminated tiles do not negatively influence the retrieval result. The presented computer-aided tile consulting system retrieves tiles from recent tile production digital catalogues, so that the retrieved tiles have as similar pattern and/or colours to a query tile as possible. The system is verified on a large commercial tile database in a psychovisual experiment.