In this paper we introduce Improved Opponent Colour Local Binary Patterns (IOCLBP), a conceptually simple yet effective descriptor for colour texture classification. The method was experimentally validated over eight datasets of colour texture images. The results show that IOCLBP outperformed other LBP variants and was at least as effective as last generation features from Convolutional Neural Networks.
Bianconi, F., Bello Cerezo, R., Napoletano, P., Di Maria, F. (2017). Improved opponent colour local binary patterns for colour texture classification. In Computational Color Imaging (pp.272-281). Springer Verlag [10.1007/978-3-319-56010-6_23].
Improved opponent colour local binary patterns for colour texture classification
Napoletano, P;
2017
Abstract
In this paper we introduce Improved Opponent Colour Local Binary Patterns (IOCLBP), a conceptually simple yet effective descriptor for colour texture classification. The method was experimentally validated over eight datasets of colour texture images. The results show that IOCLBP outperformed other LBP variants and was at least as effective as last generation features from Convolutional Neural Networks.
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