Paper
1 May 2003 Using a CBIR scheme based on experts knowledge for a computer-aided classification of ornamental stones
Author Affiliations +
Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.514960
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States
Abstract
This paper aims to present a complete methodology based on a multidisciplinary approach, that combines the extraction of low-level features to describe images in a high-level concept or formalism dedicated to Computer-Aided Categorization of ornamental stones (granite, marble). The problem is resolved thanks to a Content-Based Image Retrieval scheme where each image from the ornamental database is represented by a features vector. This last is composed, on one hand, by a color feature corresponding to a novel characterization of color histogram and on the other hand by a texture feature corresponding to a color-based co-occurrence matrix from where we extract some feature representation. The combination of both color texture descriptors is done thanks to a stage of expert know-how extraction. This know-how is represented by the way of weighting factors and confidence degrees. The fusion of the whole data allows to improve the categorization performances.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohamed-Chaker Larabi, Noel Richard, Olivier Colot, and C. Fernandez "Using a CBIR scheme based on experts knowledge for a computer-aided classification of ornamental stones", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.514960
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KEYWORDS
Databases

Feature extraction

Image retrieval

Matrices

Quantization

RGB color model

Image classification

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