Implicit Concept-based Image Indexing and Retrieval for Visual Information Systems

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AZZAM, Ibrahim Ahmed Aref-thesis.pdf

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http://eprints.org/relation/isVersionOf https://vuir.vu.edu.au/id/dark_document/60519 http://eprints.org/relation/isVolatileVersionOf https://vuir.vu.edu.au/id/dark_document/60519 http://eprints.org/relation/issmallThumbnailVersionOf https://vuir.vu.edu.au/id/dark_document/60519 archive 34 disk0/00/00/04/79 2007-05-30 2021-08-27 07:39:46 2020-07-17 05:00:02 thesis show Azzam Ibrahim Ahmed Aref Azzam, Ibrahim Ahmed Aref Implicit Concept-based Image Indexing and Retrieval for Visual Information Systems unpub 280000 FOR_2008_080100 tafeengineering image indexing; image retrieval; visual information systems; concept-based models; objects This thesis focuses on Implicit Concept-based Image Indexing and Retrieval (ICIIR), and the development of a novel method for the indexing and retrieval of images. Image indexing and retrieval using a concept-based approach involves extraction, modelling and indexing of image content information. Computer vision offers a variety of techniques for searching images in large collections. We propose a method, which involves the development of techniques to enable components of an image to be categorised on the basis of their relative importance within the image in combination with filtered representations. Our method concentrates on matching subparts of images, defined in a variety of ways, in order to find particular objects. The storage of images involves an implicit, rather than an explicit, indexing scheme. Retrieval of images will then be achieved by application of an algorithm based on this categorisation, which will allow relevant images to be identified and retrieved accurately and efficiently. We focus on Implicit Concept-based Image Indexing and Retrieval, using fuzzy expert systems, density measure, supporting factors, weights and other attributes of image components to identify and retrieve images. 2006 submitted 60519 2 2393713 dark_document 60519 Azzam, Ibrahim.pdf application/pdf 6f3ad1bbb147b6a22c19e62a8077be4d MD5 41053 2020-08-19 03:56:39 479 7 7 application/pdf text VURR permission form en staffonly

Azzam, Ibrahim.pdf

other public 330 Victoria University School of Computer and Mathematical Sciences phd phd Includes bibliographical references pp. 258-275 FALSE