Multiresolution Image Parametrization for Improving Texture Classification. (12th December 2007)

• Record Type: Journal Article
• Authors: Šajn Šajn, Luka Luka; Kononenko Kononenko, Igor Igor
• Other Names: Charrier Charrier C. C. Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2007-12-12
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/617457
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : In the paper an innovative alternative to automatic image parametrization on multiple resolutions, based on texture description with specialized association rules, and image evaluation with machine learning methods is presented. The algorithm ArTex for parameterizing textures with association rules belonging to structural parametrization algorithms was developed. In order to improve the classification accuracy a multiresolution approach is used. The algorithm ARes for finding more informative resolutions based on the SIFT algorithm is described. The presented algorithms are evaluated on several public domains and the results are compared to other well-known parametrization algorithms belonging to statistical and spectral parametrization algorithms. Significant improvement of classification results was observed when combining parametrization attributes at several image resolutions for most parametrization algorithms. Our results show that multiresolution image parametrization should be considered when improvement of classification accuracy in textural domains is required. These resolutions have to be selected carefully and may depend on the domain itself.