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Texture features and segmentation based on multifractal approach

Abstract : In this paper, we use a multifractal approach based on the computation of two spectrums for image analysis and texture segmentation problems. The two spectrums are the Legendre Spectrum, determined by classical methods, and the Large Deviation Spectrum, determined by kernel density estimation. We propose a way for the fusion of these two spectrums to improve textured image segmentation results. An unsupervised k-means is used as clustering approach for the texture classification. The algorithm is applied on mosaic image built using IKONOS images and various natural textures from the Brodatz album. The segmentation obtained with our approach gives better results than the application of each spectrum separately.
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Contributor : Enguerran Grandchamp <>
Submitted on : Tuesday, June 21, 2011 - 10:02:35 PM
Last modification on : Wednesday, September 5, 2018 - 1:30:05 PM


  • HAL Id : hal-00602268, version 1



Enguerran Grandchamp, Abadi Mohamed. Texture features and segmentation based on multifractal approach. CIARP, Nov 2006, Cancun, Mexico. pp.1. ⟨hal-00602268⟩



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