Content Based Image Retrieval Using Category-Based Indexing
Currently, most content based image retrieval (CBIR) systems operate on all images, without sorting images into different types or categories. Different images have different characteristics and thus often require different analysis techniques and query types. Additionally, placing an image into a category can help the user to navigate retrieval results more effectively. To categorise an image, firstly the dominant region needs to be extracted using multi level colour segmentation. Based on the regions’ features of colour, texture, shape and relation between regions, the image is then categorised. Users are presented with retrieval results sorted into different categories, where dominant region extraction will allow for object based retrieval to be performed.
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|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2004 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||18 Oct 2005|
|Last Modified:||09 Jun 2010 12:23|
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