Texture classification using dual-tree complex wavelet transform

S.Hatipoglu, S.K.Mitra and N. Kingsbury
University of California, Santa Barbara, CA, USA 93106-9560


A new texture feature extraction method utilizing dual tree complex wavelet transform (DT-CWT) is introduced. The complex wavelet. transform is a recently developed tool that uses a dual tree of wavelet filters to find the real and imaginary parts of complex wavelet, coefficients (1). Approxin1ate shift. invariance, good directional selectivity, computational efficiency properties of DT-CWT make it a good candidate for representing the texture features. In this paper, we propose a method for efficiently using the properties of DT-CWT in finding the directional and spatial/frequency characteristics of the patterns and classifying different texture patterns in terms of these characteristics. Experimental results show that the proposed feature extraction and classi- fication method is efficient, in terms of computational speed and retrieval accuracy.
[PDF] [BibTex]
S.Hatipoglu, S.K.Mitra and N. Kingsbury,
Seventh International Conference on Image Processing and Its Applications, vol. 1, no. 2, pp. 344-7, Manchester, UK, Jul. 1999.
Node ID: 299 , DB ID: 96 , Lab: IPL , Target: Conference
Subject: [IPL] « Look up more