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Using color image processing techniques to improve the performance of content-based image retrieval systems

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Date Issued:
2001
Summary:
A Content-Based Image Retrieval (CBIR) system is a mechanism intended to retrieve a particular image from a large image repository without resorting to any additional information about the image. Query-by-example (QBE) is a technique used by CBIR systems where an image is retrieved from the database based on an example given by the user. The effectiveness of a CBIR system can be measured by two main indicators: how close the retrieved results are to the desired image and how fast we got those results. In this thesis, we implement some classical image processing operations in order to improve the average rank of the desired image, and we also implement two object recognition techniques to improve the subjective quality of the best ranked images. Results of experiments show that the proposed system outperforms an equivalent CBIR system in QBE mode, both from the point of view of precision as well as recall.
Title: Using color image processing techniques to improve the performance of content-based image retrieval systems.
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Name(s): Costa, Fabio Morais.
Florida Atlantic University, Degree grantor
Furht, Borko, Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2001
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 125 p.
Language(s): English
Summary: A Content-Based Image Retrieval (CBIR) system is a mechanism intended to retrieve a particular image from a large image repository without resorting to any additional information about the image. Query-by-example (QBE) is a technique used by CBIR systems where an image is retrieved from the database based on an example given by the user. The effectiveness of a CBIR system can be measured by two main indicators: how close the retrieved results are to the desired image and how fast we got those results. In this thesis, we implement some classical image processing operations in order to improve the average rank of the desired image, and we also implement two object recognition techniques to improve the subjective quality of the best ranked images. Results of experiments show that the proposed system outperforms an equivalent CBIR system in QBE mode, both from the point of view of precision as well as recall.
Identifier: 9780493421971 (isbn), 12870 (digitool), FADT12870 (IID), fau:9744 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 2001.
Subject(s): Image processing--Digital techniques
Imaging systems--Image quality
Information storage and retrieval systems
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12870
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.