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Pacific-Rim Conference on Multimedia

PCM 2013: Advances in Multimedia Information Processing – PCM 2013 pp 856–865Cite as

Compact and Robust Image Fingerprints Based on CCA of Local Features

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8294))

Abstract

Image fingerprints are perceptual features or short summaries of a given image. They can be used for identifying image contents just as human fingerprints are used for identification. In this paper, we propose a novel compact image fingerprint extraction method based on canonical correlation analysis (CCA) of local features. After extraction of local SIFT features, we first divide the 128-dimension feature into two segments to form two closely related feature matrices for a given image. Then we apply CCA to the two matrices, and take the quantized canonical coefficient matrix (8×8) as the image fingerprint which is very compact, only 64 bytes for any image of arbitrary size. Experimental results show that the proposed method is discriminative and robust against both normal image processing operations such as compression common geometric transformations including cropping, scaling, and rotation.

This work was supported by Science and Technology Program of Hunan Province (2012FJ3035) and National Natural Science Foundation of China (61272214).

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Author information

Authors and Affiliations

  1. School of Computer and Communication, Hunan University of Technology, Zhuzhou, Hunan, 412008, China

    Yang Jing

  2. School of Civil Engineering, Hebei University of Engineering, Handan, Hebei, 056038, China

    Yang Jing

  3. School of Electronic and Information Engineering, Liaoning University of Technology, Jinzhou, 121001, China

    Fuming Sun

Authors
  1. Yang Jing
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  2. Fuming Sun
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Editor information

Editors and Affiliations

  1. EURECOM, Multimedia Department, Sophia Antipolis, France

    Benoit Huet

  2. Department of Computer Science, City University of Hong Kong, Tat Chee Ave, Kowloon, Hong Kong

    Chong-Wah Ngo

  3. Nanjing University of Science and Technology, 210093, Nanjing, China

    Jinhui Tang

  4. Department of Computer Science and Technology, Nanjing University, Xianlin Avenue No. 163, 210023, Nanjing, China

    Zhi-Hua Zhou

  5. School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

    Alexander G. Hauptmann

  6. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117583, Singapore, Singapore

    Shuicheng Yan

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© 2013 Springer International Publishing Switzerland

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Jing, Y., Sun, F. (2013). Compact and Robust Image Fingerprints Based on CCA of Local Features. In: Huet, B., Ngo, CW., Tang, J., Zhou, ZH., Hauptmann, A.G., Yan, S. (eds) Advances in Multimedia Information Processing – PCM 2013. PCM 2013. Lecture Notes in Computer Science, vol 8294. Springer, Cham. https://doi.org/10.1007/978-3-319-03731-8_80

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  • DOI: https://doi.org/10.1007/978-3-319-03731-8_80

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03730-1

  • Online ISBN: 978-3-319-03731-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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