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An Investigation of fSVD and Ridgelet Transform for Illumination and Expression Invariant Face Recognition

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Advances in Intelligent Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 320))

Abstract

This paper presents a wide-eyed yet effective framework for face recognition based on the combination of flustered SVD(fSVD) and Ridgelet transform. To this end we meliorate in the sense of computation efficiency, invariant to facial expression and illumination of [21]. Firstly fSVD is applied to an image by modelling SVD and selecting a proportion of modelled coefficients to educe illumination invariant image. Further, Ridgelet is employed to extract discriminative features exhibiting linear properties at different orientations by representing smoothness along the edges of flustered image and also to map line singularities into point singularities, which improves the low frequency information that is useful in face recognition. PCA is used to project higher dimension feature vector onto a low dimension feature space to increase numerical stability. Finally, for classification five different similarity measures are used to obtain an average correctness rate. We have demonstrated our proposed technique on widely used ORL dataset and achieved high recognition rate in comparision with several state of the art techniques.

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Authors and Affiliations

  1. SJB Institute of Technology, Bengaluru, 560060, India

    Belavadi Bhaskar, K. Mahantesh & G. P. Geetha

Authors
  1. Belavadi Bhaskar
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  2. K. Mahantesh
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  3. G. P. Geetha
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Corresponding author

Correspondence to Belavadi Bhaskar .

Editor information

Editors and Affiliations

  1. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

  2. Indian Institute of Information Technology and Management- - Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  3. Faculty of Design, Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  4. Department of Information Systems and Operations Management, University of Florida, Warrington College of Business, Florida, Florida, USA

    Selwyn Piramuthu

  5. University of Applied Sciences, Institute for Information Systems, Olten, Switzerland

    Thomas Hanne

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© 2015 Springer International Publishing Switzerland

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Bhaskar, B., Mahantesh, K., Geetha, G.P. (2015). An Investigation of fSVD and Ridgelet Transform for Illumination and Expression Invariant Face Recognition. In: El-Alfy, ES., Thampi, S., Takagi, H., Piramuthu, S., Hanne, T. (eds) Advances in Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-319-11218-3_4

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  • DOI: https://doi.org/10.1007/978-3-319-11218-3_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11217-6

  • Online ISBN: 978-3-319-11218-3

  • eBook Packages: EngineeringEngineering (R0)

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