Salient-Object-Based Image Query by Visual Content

Amenu, Dawit Bulcha (2004) Salient-Object-Based Image Query by Visual Content. Masters thesis, Addis Ababa University.

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Abstract

The rise in the intense utilization of images in our daily life resulted in a high volume of images produced from different sectors of human endeavor. This resulted in the need for an efficient management of image data. Recently, Content-based image retrieval has attracted much attention from the research community. As exact matching is not possible with image retrieval, the approach is to use similarity-based matching. Much of the works on similaritybased image retrieval use the global features (color, shape, texture, etc) of the entire image to compute similarity score between two images. Equally important to using the entire image is the use of salient-objects; objects in an image that are of particular interest to the user, as the basis of similarity-based computation. The current works on content-based image retrieval do not address very well the issues related to salient-objects based image retrieval. In this work, we have proposed an extension to a previous work on image database modeling and query processing. To support salient object based image retrieval, we have proposed an extension of the data repository model so that spatial features of contained salient objects are captured. Moreover, we proposed an extension to the similarity-based selection operator defined earlier so that salient object based selection operation be part of image database systems for similarity-based image retrieval. We have also proposed spatial operators that can be used to compute spatial relation between an image and contained salient objects. We have reviewed and presented refined formulations of previous works on spatial relations between objects in 2D space to compute spatial relation between salient objects. To demonstrate the viability of salient-objects-based image retrieval, we have extended a previous work named EMIMS, to develop a system named EMIMS-S (Extended Medical Image Management System to support Salient objects). We have also used this prototype to experimentally show the retrieval effectiveness of salient-objects-based image queries.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Salient-object-based image retrieval, similarity of salient-objects, image database, image data model, similarity-based algebra, spatial relation of salient-objects.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Africana
Depositing User: Selom Ghislain
Date Deposited: 02 Oct 2018 08:55
Last Modified: 02 Oct 2018 08:55
URI: http://thesisbank.jhia.ac.ke/id/eprint/5748

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