Rotation invariant texture classification using modified Gabor filters

G.M.Haley* and B.S.Manjunath**

* California Microwave, Incorporated
6022 Variel Ave.
Woodland Hills, CA 91367 USA

** Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106 USA


A method of rotation invariant texture classification based on a joint space-frequency model is introduced. Multiresolution filters, based on a truly analytic form of a polar 2-D gabor wavelet, are used to compute spatial frequency-specific but spatially localized microfeatures. These microfeatures constitute an approximate basis set for the represntation of the texture sample. The essential characteristics of a texture sample, its macrofeatures, are derived from the statistics of its microfeatures. A texture is modeled as a multivariate Gaussian distribution of macrofeatures. Classification is based on a rotation invariant subset of macrofeatures.
[PDF] [BibTex]
G. M. Haley and B. S. Manjunath,
Second IEEE international conference on image processing (ICIP'95), vol. 1, pp. 262-265, Washington, D.C., Nov. 1995.
Node ID: 237 , DB ID: 31 , VRLID: 28 , Lab: VRL , Target: Proceedings
Subject: [Image Texture] « Look up more