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Gender Classification Using Local Binary Pattern and Particle Swarm Optimization

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Emerging Trends and Applications in Information Communication Technologies (IMTIC 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 281))

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Abstract

Gender classification is the phenomena in which a face image is analyzed and recognized by a computer. Feature extraction is the key step of gender classification. In this paper, we present a method which efficiently classifies gender by extracting the key optimized features. We have used Local Binary Pattern (LBP) to extract facial features. As LBP features contain many redundant features, Particle Swarm Optimization (PSO) was applied to get optimized features. We performed different numbers of experiments on FERET face database and report 95.5 % accuracy.

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Author information

Authors and Affiliations

  1. Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan

    Sajid Ali Khan, Naveed Riaz & M. Hussain

  2. UIIT-PMAS University of Arid Agriculture, Rawalpindi, Pakistan

    Muhammad Nazir & Nawazish Naveed

Authors
  1. Sajid Ali Khan
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  2. Muhammad Nazir
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  3. Naveed Riaz
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  4. M. Hussain
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  5. Nawazish Naveed
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Editor information

Editors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Faculty of Electrical, Electronics & Computer Engineering, Mehran UET, Jamshoro, Pakistan

    Bhawani Shankar Chowdhry

  2. Department of Telecommunication Engineering, Mehran University of Engineering and Technology, 76062, Jamshoro, Sindh, Pakistan

    Faisal Karim Shaikh

  3. Department of Software Engineering & Media Technology, Aalborg University, Niels Bohrs Vej 8, 6700, Esbjerg, Denmark

    Dil Muhammad Akbar Hussain

  4. Department of Electrical Engineering, Mehran University of Engineering and Technology, 76062, Jamshoro, Sindh, Pakistan

    Muhammad Aslam Uqaili

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© 2012 Springer-Verlag Berlin Heidelberg

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Khan, S.A., Nazir, M., Riaz, N., Hussain, M., Naveed, N. (2012). Gender Classification Using Local Binary Pattern and Particle Swarm Optimization. In: Chowdhry, B.S., Shaikh, F.K., Hussain, D.M.A., Uqaili, M.A. (eds) Emerging Trends and Applications in Information Communication Technologies. IMTIC 2012. Communications in Computer and Information Science, vol 281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28962-0_8

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  • DOI: https://doi.org/10.1007/978-3-642-28962-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28961-3

  • Online ISBN: 978-3-642-28962-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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