Optimization of Spatial Filters for Image Texture Feature Separation
by Simulated Annealing
Frode Nergård and
Trygve Randen
Høgskolen i Stavanger
P.O. Box 2557 Ullandhaug, N-4004 Stavanger, Norway
In Proc. NORSIG, Helsinki, Finland, September 1996, pp. 251-254
Full paper
Abstract
In a work by Randen and Husøy, an approach to the design of
filters for texture feature extraction for two textures has been developed.
The feature extraction process were modelled as a filter with a subsequent
local energy function.
The filter was optimized with respect to a criterion of obtaining high
distance between the modelled feature means and low modelled feature
variances.
However, the optimization was based on some simplifying assumptions.
Using the same criterion, without making these simplifications, we propose
three methods for finding the optimal filter.
All methods have their basis in simulated annealing, and one of them, called
annealing evolution, are also based on genetic algorithms.
Experiments indicate that the suggested methods were able to find better
filters than the methods proposed by Randen and Hus{\o}y.