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Compact feature vector for natural texture classification

Conference Paper


Abstract


  • Gabor filter masks are used to extract succinct feature vectors from natural and synthetic textures. Textures from the Brodatz collection and real images, captured through a CCD camera, are used in the experiment. The results obtained represent a high accuracy of classification for those textures with pronounced orientation. Classification accuracy up to 90% is obtained using 50-fealure vector. A lower classification accuracy is obtained with a 20-feature vector (about 70%), due to the fact that the orientation-space is not finely sampled so as to capture all the possibilities. These results compare well, with results obtained using the same method on computer generated artificial textures.

Publication Date


  • 1995

Citation


  • Naghdy, G. A., Tanbe, M., & Ogunbona, P. O. (1995). Compact feature vector for natural texture classification. In ANZIIS 1995 - Proceedings of the 3rd Australian and New Zealand Conference on Intelligent Information Systems (pp. 59-63). doi:10.1109/ANZIIS.1995.705715

Scopus Eid


  • 2-s2.0-85063529185

Web Of Science Accession Number


Start Page


  • 59

End Page


  • 63

Volume


Issue


Place Of Publication


Abstract


  • Gabor filter masks are used to extract succinct feature vectors from natural and synthetic textures. Textures from the Brodatz collection and real images, captured through a CCD camera, are used in the experiment. The results obtained represent a high accuracy of classification for those textures with pronounced orientation. Classification accuracy up to 90% is obtained using 50-fealure vector. A lower classification accuracy is obtained with a 20-feature vector (about 70%), due to the fact that the orientation-space is not finely sampled so as to capture all the possibilities. These results compare well, with results obtained using the same method on computer generated artificial textures.

Publication Date


  • 1995

Citation


  • Naghdy, G. A., Tanbe, M., & Ogunbona, P. O. (1995). Compact feature vector for natural texture classification. In ANZIIS 1995 - Proceedings of the 3rd Australian and New Zealand Conference on Intelligent Information Systems (pp. 59-63). doi:10.1109/ANZIIS.1995.705715

Scopus Eid


  • 2-s2.0-85063529185

Web Of Science Accession Number


Start Page


  • 59

End Page


  • 63

Volume


Issue


Place Of Publication