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BFO-RLDA: A New Classification Scheme for Face Images Using Probabilistic Reasoning Model

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8297))

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Abstract

Regularized-LDA (R-LDA) is a LDA-based method used for finding the nonzero eigenvalues and the corresponding eigenvectors. This paper presents a RLDA-based classification of face images which uses bacteria foraging optimization (BFO) algorithm for selecting the optimal discriminating features. The optimal features are then used by probabilistic reasoning model for classification of unknown face images. The ORL and the UMIST databases are used for experiment to demonstrate the performance of our proposed method. It is observed that our proposed method outperforms the existing method.

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Author information

Authors and Affiliations

  1. Electrical & Electronics Engineering Department, VSS University of Technology, Burla, Odisha, India

    Lingraj Dora

  2. Electronics & Telecommunication Engineering Department, VSS University of Technology, Burla, Odisha, India

    Sanjay Agrawal & Rutuparna Panda

Authors
  1. Lingraj Dora
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  2. Sanjay Agrawal
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  3. Rutuparna Panda
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Editor information

Editors and Affiliations

  1. Electrical Engineering Dept., IIT Delhi, Hauz Khas, 110016, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, 700108, Kolkata, India

    Swagatam Das

  4. SRM Engineering College, Department of Electrical and Electronics Engineering, SRM University, Potheri, Kattankulathur, Kancheepuram, 603203, Tamil Nadu, India

    Shubhransu Sekhar Dash

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© 2013 Springer International Publishing Switzerland

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Dora, L., Agrawal, S., Panda, R. (2013). BFO-RLDA: A New Classification Scheme for Face Images Using Probabilistic Reasoning Model. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8297. Springer, Cham. https://doi.org/10.1007/978-3-319-03753-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-03753-0_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03752-3

  • Online ISBN: 978-3-319-03753-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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