Title: Rock Image Classification Using Non-Homogenous Textures and Spectral Imaging
Authors: Lepistö, Leena
Kunttu, Iivari
Autio, Jorma
Visa, Ari
Citation: WSCG ’2003: Short papers: The 11-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2003, 3.-7, p. 82-86.
Issue Date: 2003
Publisher: UNION Agency
Document type: konferenční příspěvek
URI: http://wscg.zcu.cz/wscg2003/Papers_2003/D43.pdf
ISBN: 80-903100-1-X
Keywords: klasifikace textur;nehomogenní textury;spektrální zobrazování;skála
Keywords in different language: texture classification;non-homogenous texture;spectral imaging;rock
Abstract: Texture analysis and classification are usual tasks in pattern recognition. Rock texture is a demanding classification task, because the texture is often non-hom ogenous. In this paper, we introduce a rock texture classification method, which is based on textural and spectral features of the rock. The spectral features are considered as some color parameters whereas the textural features are calculated from the co-occurrence matrix. In this classification method, non-homogenous texture imag es are divided into blocks. The feature values are calculated for each block separately. In this way, the feature values of the texture image can be presented as a feature histogram. The classification method is tested using two types of rock textures. The experimental results show that the proposed features are able to distinguish rock textures quite well.
Rights: © UNION Agency
Appears in Collections:WSCG '2003: Short papers

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