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\title{Wavelets, Signal Processing and Textile Surfaces}
\author{Holger Kraus\\
Department of Textiles and Fashion \\
School of Design and Manufacture \\
De Montfort University, United Kingdom}
\date{}
\maketitle

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In recent years, wavelet transform has been introduced as a mathematical tool to the field of signal and image processing and has attracted great attention (Wavelets for a Vision, Mallat, 1996). \\

\noindent

In this paper, a brief introduction of the concept of signal transforms with particular reference to Fourier transform as a frequency representation tool of a signal is given. After explaining the need for a time--frequency representation, especially for non-stationary signals, further progress to the windowed Fourier transform including its merits and in particular limitations due to Heisenberg's uncertainty principle is made. This leads to the introduction of the wavelet transform with its multiresolution capability. \\

\noindent

This paper then provides a summary on the use of the wavelet transform in combination with some signal processing methods that have been designed in an attempt to characterise and classify texture of textile fabrics as well as to detect defects more speedily and accurately than conventional techniques. This paper aims to raise research interest in the application of wavelet transform for the analysis and description of textile surfaces and the design of appropriate classification algorithms for unsupervised processing of textile image data. \\

\noindent

Past work shows that the integration of multi-resolution information gained from wavelet transformed images in classification algorithms is not a straightforward process and there are many opportunities for new research ideas.


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Contact details:
Mr. Holger Kraus
School of Design and Manufacture
De Montfort University
The Gateway
Leicester, LE1 9BH, England
Tel. +44-802-60 65 70, Fax +44-116-255 1195
E-mail hka@dmu.ac.uk


