Multichannel filtering for image texture segmentation
Trygve Randen
(e-mail: tranden@hsr.no)
John Håkon Husøy (e-mail: jonh@hsr.no)
Rogaland University Center
Department of Electrical and Computer Engineering
P.O. Box 2557 Ullandhaug, N-4004 Stavanger, Norway
Phone: +47 51 87 40 00
Fax: +47 51 87 42 36
Optical Engineering, vol. 33, no. 8, August 1994, pp. 2617-2625
Full paper
Abstract
Several approaches to multichannel filtering for texture classification
and segmentation with Gabor filters have been proposed.
The rationale presented for the use of the Gabor filters is their relation to
models for the early vision of mammals as well as their joint optimum
resolution in time and frequency.
In this work we present a critical evaluation of the Gabor filters as
opposed to filter banks used in image coding -- in both
full rate and critically sampled realizations.
In the critically sampled case, tremendous computational savings can be
realized.
We further evaluate the commonly used octave band decomposition versus
alternative decompositions.
We conclude that, for a texture segmentation task, several filters provide
approximately the same results as the Gabor filter and, most important, it
is possible to use sub-sampled filters with only a modest degradation in
segmentation accuracy -- realizing considerable computational savings.