Texture Recognition through Modal Analysis of Spectral Peak Patterns

In this paper we investigate how texture recognition can be achieved through the modal analysis of the pattern of peaks in the spectral density function. We commence from a texture characterisation which is based on the positions of peaks in the power spectrum. Our aim is to use the modal structure of the pattern of peaks to perform texture retrieval from an image data-base. We explore two different approaches to the problem. First, we use a variant of the Shapiro and Brady method to perform recognition by comparing the modal structure of the proximity matrix for peak cluster centres. Second, we perform latent semantic indexing on vectors representing the polar distribution of frequency peaks. We provide and experimental evaluation of these two methods on a data-base of fabric and wrapping paper patterns.