Ms. Aniza Othman Profile

Aniza Othman

at Univ of Southampton

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Proceedings Article | 28 January 2008 Paper

Colour appearance descriptors for image browsing and retrieval

Aniza Othman, Kirk Martinez

Proceedings Volume 6820, 68200R (2008) https://doi.org/10.1117/12.766882

KEYWORDS: Image retrieval, Image classification, Classification systems, Chromium, Image compression, Photography, Algorithm development, Colorimetry, Feature extraction, Visualization

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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 whole-scene 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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