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    An integrated aurora image retrieval system: AuroraEye

    Fu, R. and Gao, X. and Li, Xuelong and Tao, D. and Jiang, Y. and Li, J. and Hussmann, H. and Yang, H. (2010) An integrated aurora image retrieval system: AuroraEye. Journal of Visual Communication and Image Representation 21 (8), pp. 787-797. ISSN 10473203.

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    Abstract

    With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): Content-based image retrieval; Aurora; Adaptive LBP; Gabor; image texture analysis, database, feature extraction, local binary pattern
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 20 Jun 2013 13:25
    Last Modified: 11 Oct 2016 15:27
    URI: https://eprints.bbk.ac.uk/id/eprint/7540

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