Fuzzy Fusion of Colour and Shape Features for Efficient Image Retrieval

Aboaisha, Hosain, Xu, Zhijie and El-Feghi, Idris (2010) Fuzzy Fusion of Colour and Shape Features for Efficient Image Retrieval. In: Future Technologies in Computing and Engineering: Proceedings of Computing and Engineering Annual Researchers' Conference 2010: CEARC’10. University of Huddersfield, Huddersfield, pp. 31-36. ISBN 9781862180932

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Abstract

Content Based Image Retrieval (CBIR) based on colour has been subjecting to research for many years. While partially successful in resolving some important theoretical and practical problems, it is also becoming clear that other sensory elements will also play the vital part as the supplementary signal inputs in enabling better
judgements on digital imagery. For example, geometry shapes will provide important topological information on the image contents. On contrary to colour stimuli, image retrieval based on shapes is still relatively immature. This is due to the complexity and ambiguity on shape definition and the infinite possibility on shape
combinations. In this paper, an innovative approach based on fuzzy fusion of colours and shapes for image retrieval is presented. In this work, the so-called feature vector will play a pivotal role in streamlining the colour and shape features based on the Pseudo Zernike Moments (PZM) for improving the efficiency and accuracy of a CBIR system.

Item Type:	Book Chapter
Uncontrolled Keywords:	Fuzzy Colour histogram, Conventional Colour Histogram, Fusion of colour and Shape, Pseudo Zernike Moments
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Schools:	School of Computing and Engineering School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC) School of Computing and Engineering > High-Performance Intelligent Computing > Visualisation, Interaction and Vision
Related URLs:	Author
Depositing User:	Sharon Beastall
Date Deposited:	13 Jan 2011 09:22
Last Modified:	28 Aug 2021 21:48
URI:	http://eprints.hud.ac.uk/id/eprint/9311

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