M. Latifi, M. Amani, S. M. Etrati and A. H. Sadri,
Volume 23, Issue 1 (7-2004)
Abstract
Quality control of textile products is an important stage in textile industries. To this end, the conventional method in fault detection is human inspection. In the present work, Wavelet transform was applied on images of simple circular knitted fabrics to diagnose five regular defects. The results showed that the method applied was accurate and fast in addition to being capable of determining fault position and dimensions. Therefore, the Wavelet transform method is suitable for online fault detection
H. Saeedi, M. Modarres-Hashemi and S. Sadri,
Volume 24, Issue 1 (7-2005)
Abstract
With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection methods, the interference is firstly canceled and then a simple detector, like an energy detector, is
used. Therefore, we have used wavelet-based approaches to cancel the interference and then an energy detector has been employed. In this paper, it is shown that in practical cases where the performance of matched filter or near-matched filter is degraded, wavelet-based methods are more efficient. Also, we have shown that for cases where targets with slow radial velocity or one close to blind velocity are removed by the MTI filter, wavelet-based denoising has a better performance.
