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Face Recognition with Quantum Associative Networks Using Overcomplete Gabor Wavelet

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Abstract

Gabor wavelet is considered the best mathematical descriptor for receptive fields in the striate cortex. Besides, as a basis function, it is suitable to sparsely represent natural scenes due to its property in maximizing information. It is argued that Gabor-like receptive fields are emerged by sparseness-enforcing or infomax method. In this paper, we incorporate Gabor overcomplete representation into quantum holography for image recognition tasks, with suggestions in improvements through iterative method for reconstruction.

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Authors and Affiliations

  1. Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia

    Nuo Wi Tay & Chu Kiong Loo

  2. Laboratory for Cognitive Modeling, FRI, University of Ljubljana, Ljubljana, Slovenia

    Mitja Peruš

Authors
  1. Nuo Wi Tay
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  2. Chu Kiong Loo
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  3. Mitja Peruš
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Correspondence to Chu Kiong Loo.

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Tay, N.W., Loo, C.K. & Peruš, M. Face Recognition with Quantum Associative Networks Using Overcomplete Gabor Wavelet. Cogn Comput 2, 297–302 (2010). https://doi.org/10.1007/s12559-010-9047-2

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  • DOI: https://doi.org/10.1007/s12559-010-9047-2

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