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Colour appearance descriptors for image browsing and retrieval

Colour appearance descriptors for image browsing and retrieval
Colour appearance descriptors for image browsing and retrieval
In this paper, we focus on the development of whole-scene colour appearance descriptors for classification to be used in browsing applications. The descriptors can classify a whole-scene image into various categories of semantically-based colour appearance. Colour appearance is an important feature and has been extensively used in image-analysis, retrieval and classification. By using pre-existing global CIELAB colour histograms, firstly, we try to develop metrics for wholescene colour appearance: “colour strength”, “high/low lightness” and “multicoloured”. Secondly we propose methods using these metrics either alone or combined to classify whole-scene images into five categories of appearance: strong, pastel, dark, pale and multicoloured. Experiments show positive results and that the global colour histogram is actually useful and can be used for whole-scene colour appearance classification. We have also conducted a small-scale human evaluation test on whole-scene colour appearance. The results show, with suitable threshold settings, the proposed methods can describe the whole-scene colour appearance of images close to human classification. The descriptors were tested on thousands of images from various scenes: paintings, natural scenes, objects, photographs and documents. The colour appearance classifications are being integrated into an image browsing system which allows them to also be used to refine browsing.
image processing, colour science, human perception, semantic web
Othman, Aniza
596583f0-f4ec-47c9-a2dd-7b496bd9d6f4
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18
Othman, Aniza
596583f0-f4ec-47c9-a2dd-7b496bd9d6f4
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18

Othman, Aniza and Martinez, Kirk (2008) Colour appearance descriptors for image browsing and retrieval At SPIE Electronic Imaging: Multimedia Content Access: Algorithms and Systems, United States.

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, we focus on the development of whole-scene colour appearance descriptors for classification to be used in browsing applications. The descriptors can classify a whole-scene image into various categories of semantically-based colour appearance. Colour appearance is an important feature and has been extensively used in image-analysis, retrieval and classification. By using pre-existing global CIELAB colour histograms, firstly, we try to develop metrics for wholescene colour appearance: “colour strength”, “high/low lightness” and “multicoloured”. Secondly we propose methods using these metrics either alone or combined to classify whole-scene images into five categories of appearance: strong, pastel, dark, pale and multicoloured. Experiments show positive results and that the global colour histogram is actually useful and can be used for whole-scene colour appearance classification. We have also conducted a small-scale human evaluation test on whole-scene colour appearance. The results show, with suitable threshold settings, the proposed methods can describe the whole-scene colour appearance of images close to human classification. The descriptors were tested on thousands of images from various scenes: paintings, natural scenes, objects, photographs and documents. The colour appearance classifications are being integrated into an image browsing system which allows them to also be used to refine browsing.

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More information

Published date: January 2008
Additional Information: Event Dates: 27 January
Venue - Dates: SPIE Electronic Imaging: Multimedia Content Access: Algorithms and Systems, United States, 2008-01-27
Keywords: image processing, colour science, human perception, semantic web
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 264884
URI: http://eprints.soton.ac.uk/id/eprint/264884
PURE UUID: 464d7b2c-b002-408d-a400-06bfe4a8d455
ORCID for Kirk Martinez: ORCID iD orcid.org/0000-0003-3859-5700

Catalogue record

Date deposited: 21 Nov 2007 11:26
Last modified: 18 Jul 2017 07:31

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Contributors

Author: Aniza Othman
Author: Kirk Martinez ORCID iD

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