Paper Details: Downloads: 451
Serial Number: P1150442010
Title: Image Retrieval using Local Colour and Texture Features
Authors: Ibrahim El-Henawy and Mohamed Eisa and A. E. Elalfi and Hans Burkhardt
Abstract: Colour histograms proved to be successful in automatic image retrieval; however, their draw back is that all structural information is lost. Therefore Siggelkow et al. extended the colour histogram approach by features that take into account the relations within a local pixel neighbourhood. They extracted features that are invariant with respect to translation and rotation by integrating nonlinear functions over the group of Euclidean motion. Gabor wavelets proved to be very useful texture analysis. In this paper we present an image retrieval method based on nonlinear monomial kernel function and Gabor filters. Colour features are found by calculating the 3D colour histogram after applying the monomial kernel function on the image. Texture features are found by calculating the mean and standard deviation of the Gabor filtered image. Experimental results are shown and discussed.
Keywords: Image Retrieval, Knowledge Discovery, Data Mining, Colour Histograms, Intelligent Agent.
Journal/Conference: International Journal of Graphics, Vision and Image Processing
Volume: 5
Issue: SI1
Submission Date: 1/1/2005 12:00:00 AM
Review Date: 3/1/2005 12:00:00 AM
Publishing Date: 5/1/2005 12:00:00 AM
Article Downloads: 451
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