Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2009.5414273
Title: Wavelet leader multifractal analysis for texture classification
Authors: Wendt, H.
Abry, P.
Jaffard, S.
Ji, H. 
Shen, Z. 
Keywords: Image classification
Image multifractal analysis
Texture characterization
Wavelet leader
Issue Date: 2009
Citation: Wendt, H., Abry, P., Jaffard, S., Ji, H., Shen, Z. (2009). Wavelet leader multifractal analysis for texture classification. Proceedings - International Conference on Image Processing, ICIP : 3829-3832. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2009.5414273
Abstract: Image classification often relies on texture characterization. Yet texture characterization has so far rarely been based on a true 2D multifractal analysis. Recently, a 2D wavelet Leader based multifractal formalism has been proposed. It allows to perform an accurate, complete and low computational and memory costs multifractal characterization of textures in images. This contribution describes the first application of such a formalism to a real large size (publicly available) image database, consisting of 25 classes of non traditional textures, with 40 high resolution images in each class. Multifractal attributes are estimated from each image and used as classification features within a standard k nearest neighbor classification procedure. The results reported here show that this Leader based multifractal analysis enables the effective discrimination of different textures, as performances in both classification scores and computational costs compare favorably against those of procedures previously proposed in the literature on the same database. ©2009 IEEE.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/104654
ISBN: 9781424456543
ISSN: 15224880
DOI: 10.1109/ICIP.2009.5414273
Appears in Collections:Staff Publications

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