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An Analysis of Gabor Detection

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Image Analysis and Recognition (ICIAR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5627))

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Abstract

An elementary function that is now commonly referred to Gabor function, Gabor filter and Gabor wavelet was derived from uncertainty relation for information by Gabor to overcome the representation limit of Fourier analysis. Analyzing a signal by a Gabor filter in terms of convolution or spatial filtering, two pieces of information—phase and magnitude—can be obtained. In the paper, Gabor filter is considered as a Gabor atom detector. This analysis demonstrates that when the k-value defined as k = ∥ g ni  ∥ 2 / ∥ g nr  ∥ 2, where g nr and g ni are respectively the real and imaginary parts of a Gabor filter g n , is close to one, the target phase can be estimated by Gabor phase and the target magnitude can be estimated by Gabor magnitude. However, when the k-value decreases, the quality of this approximation also decreases. The corresponding error bounds are derived.

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Author information

Authors and Affiliations

  1. Forensics and Security Laboratory School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798

    Adams Wai-Kin Kong

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  1. Adams Wai-Kin Kong
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Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2009 Springer-Verlag Berlin Heidelberg

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Kong, A.WK. (2009). An Analysis of Gabor Detection. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_7

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  • DOI: https://doi.org/10.1007/978-3-642-02611-9_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02610-2

  • Online ISBN: 978-3-642-02611-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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