title: Rotation- and scale-invariant texture features based on spectral moment invariants.
abstract: Moment invariants previously developed for the analysis of two-dimensional patterns and objects regardless of orientation, scale, and position are extended to the Fourier transform domain to quantify signatures of textures in the power spectrum of images. The moment invariants of the power spectrum, which we call spectral moment invariants (SMIs), systematically extract rotation- and scale-invariant texture features by complex spectral moments instead of by performing ad hoc measurements of the shape of the two-dimensional power spectrum as do most of the existing Fourier transform domain methods. To our knowledge, the method of using SMIs to quantify texture features is the first to extract invariant texture information directly from the Fourier spectrum. The discriminative capability of SMIs in recognizing rotation- and scale-independent texture features is demonstrated by texture classification experiments. The results indicate that algorithms using SMIs can achieve performances comparable with, or better than, those algorithms using the spatial or wavelet transform domain texture features.
authors.affiliation: Department of Electrical and Computer Engineering, University of California at Davis, CA 95616, USA. verwang@ucdavis.edu
authors.forename: Mingshi
authors.initials: M
authors.lastname: Wang
authors.forename: André
authors.initials: A
authors.lastname: Knoesen