Segmenting modulated line textures with S-Gabor filters

Abstract

This paper describes a novel technique for segmenting frequency modulated line-textures. Textures of this sort abound in nature and are typified by growth patterns in which the deposition rate varies over time. The basic idea underpinning the technique is to use the S-Gabor kernel as a frequency modulated channel response function. According to this channel model, the central frequency changes exponentially with distance from the centre of the kernel. In order to segment the resulting texture response, we use fuzzy clustering to locate peaks in the Fourier power spectrum. In this way we estimate both the centre-frequency and the modulation parameters of the filter bank. We illustrate the effectiveness of our technique on the segmentation of growth patterns on fish scales.