Title :
Eigenvector method for texture recognition
Author :
Carcassoni, Marco ; Ribeiro, Eraldo ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
Abstract :
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.
Keywords :
eigenvalues and eigenfunctions; image recognition; image texture; spectral analysis; visual databases; Shapiro and Brady method; eigenvector method; fabric patterns; frequency peaks; image data-base; latent semantic indexing; modal structure; peak cluster centres; polar distribution; power spectrum; proximity matrix; spectral density function; texture characterisation; texture recognition; wrapping paper patterns; Autocorrelation; Computer science; Density functional theory; Frequency domain analysis; Frequency estimation; Image retrieval; Indexing; Information retrieval; Modal analysis; Pattern recognition;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1038970