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Colour appearance descriptors for image browsing and retrieval

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)


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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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


Local EPrints ID: 264884
PURE UUID: 464d7b2c-b002-408d-a400-06bfe4a8d455
ORCID for Kirk Martinez: ORCID iD

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

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Author: Aniza Othman
Author: Kirk Martinez ORCID iD

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