The image searching tool using category-based indexing
The aim of this research is to propose a new content based image retrieval (CBIR) system using categories. Different images have different characteristics and thus often require different image processing techniques. Most current CBIR systems operate on all images, without pre-sorting images into different categories. This results in limitations on retrieval performance and accuracy. Two semantic and four syntactic image categories are proposed. The category for an image is generated automatically by analysing the image for the presence of a dominant object or for correspondence to an image ‘template’. Dominant objects are obtained by performing region grouping of segmented thumbnails. The result of this research is a new Internet image retrieval and indexing system.
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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 2003 (please consult author)|
|Deposited On:||02 Mar 2005|
|Last Modified:||09 Jun 2010 12:23|
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