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Infrared Face Recognition Based on DCT and Partial Least Squares

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Advances in Image and Graphics Technologies (IGTA 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 437))

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Abstract

Infrared face imaging, being light- independent, and not vulnerable to facial skin expressions and posture, can avoid or limit the drawbacks of face recognition in visible light. However, to obtain the compact and discriminative feature extracted from infrared face image is a challenging task. In this essay, infrared face recognition method using Discrete Cosine Transform (DCT) and Partial Least Square (PLS) is proposed. Due to strong ability for data de-correlation and compact energy, DCT is studied to obtain the compact features in infrared face. To make full use of the discriminative information in DCT coefficients, the final classifier formulates PLS regression for accurate classification. The experimental results show that the proposed algorithm outperforms Principle Component Analysis (PCA) and DCT based infrared face recognition algorithms.

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Author information

Authors and Affiliations

  1. Key Lab of Optic-Electronic and Communication, Jiangxi Sciences and Technology Normal University, Nanchang, Jiangxi, 330013, China

    Zhihua Xie & Guodong Liu

Authors
  1. Zhihua Xie
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  2. Guodong Liu
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Editor information

Editors and Affiliations

  1. Chinese academy of Sciences, Beijing, China

    Tieniu Tan

  2. Beijing Jiaotong University, Beijing, China

    Qiuqi Ruan

  3. Tsinghua University, Beijing, China

    Shengjin Wang  & Huimin Ma  & 

  4. Chinese Academy of Sciences, Beijing, China

    Kaiqi Huang

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© 2014 Springer-Verlag Berlin Heidelberg

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Xie, Z., Liu, G. (2014). Infrared Face Recognition Based on DCT and Partial Least Squares. In: Tan, T., Ruan, Q., Wang, S., Ma, H., Huang, K. (eds) Advances in Image and Graphics Technologies. IGTA 2014. Communications in Computer and Information Science, vol 437. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45498-5_8

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  • DOI: https://doi.org/10.1007/978-3-662-45498-5_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45497-8

  • Online ISBN: 978-3-662-45498-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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