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Semi-automatic BPT for Image Retrieval

S. Ghanbari, and J. C. Woods, and S. M. Lucas, (2009) Semi-automatic BPT for Image Retrieval. In: 2009 Seventh International Workshop on Content-Based Multimedia Indexing, 2009-06-03 - 2009-06-05.

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Abstract

This paper presents a novel semi-automatic tool for content retrieval. A multidimension binary partition tree (BPT) is generated to perform object based image retrieval. The tree is colour based but has the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. For retrieval, a node of the query image is matched against the nodes of the BPT of the database image. These are matched according to a combination of colour histograms, texture features and edge histograms. This semi-automatic tool allows users to have more freedom in their choice of query. The paper illustrates how the use of multidimensional information can significantly enhance content retrieval results for natural images.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Notes: This paper presents a novel semi-automatic tool for content retrieval. A multidimension binary partition tree (BPT) is generated to perform object based image retrieval. The tree is colour based but has the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. For retrieval, a node of the query image is matched against the nodes of the BPT of the database image. These are matched according to a combination of colour histograms, texture features and edge histograms. This semi-automatic tool allows users to have more freedom in their choice of query. The paper illustrates how the use of multidimensional information can significantly enhance content retrieval results for natural images.
Uncontrolled Keywords: content-based retrieval; image colour analysis; image retrieval; image texture; visual databases; colour histograms; database image; edge histograms; image enhancement; multidimension binary partition tree; query image; texture features; tree nodes; Content based retrieval; Data mining; Frequency; Histograms; Humans; Image databases; Image segmentation; Information retrieval; Merging; binary partition tree
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 11 Oct 2012 13:46
Last Modified: 23 Sep 2022 18:31
URI: http://repository.essex.ac.uk/id/eprint/4052

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