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De-Noising Model for Weberface-Based and Max-Filter-Based Illumination Invariant Face Recognition

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Ubiquitous Information Technologies and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 280))

Abstract

In the topic of illumination invariant face recognition (IIFR), although the state-of-the-art Multi-scale Weberface (MSW) and Multi-scale Quotient Image (MQI) give best results against other illumination insensitive feature extraction methods, they are computationally heavy and easy affected by noises hiding in face shadow. In this paper, we propose a lightweight de-noising model to boost the IIFR system based on max-filter and Weberface called GMAX and GWEB respectively. In this model, we try to eliminate the influence of quantum noise and quantization noise on ill-illuminated images by average smoothing and Gaussian smoothing. After that, linear discriminant analysis (LDA) is adopted to improve verification rate. Never before, a comparative study on popular approaches in the literature fully implemented on the challenging data set Extended Yale B is also provided. The proposed method gives excellent results in term of both computational time and accuracy.

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Authors and Affiliations

  1. School of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea

    Hoang-Nam Bui, In-Seop Na & Soo-Hyung Kim

Authors
  1. Hoang-Nam Bui
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  2. In-Seop Na
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  3. Soo-Hyung Kim
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Corresponding author

Correspondence to Hoang-Nam Bui .

Editor information

Editors and Affiliations

  1. Department of Multimedia Engineering, Dongguk University, Seoul, Korea, Republic of (South Korea)

    Young-Sik Jeong

  2. Department of Multimedia Science, Sook Myung Women's University, Seoul, Korea, Republic of (South Korea)

    Young-Ho Park

  3. Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan

    Ching-Hsien (Robert) Hsu

  4. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

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Bui, HN., Na, IS., Kim, SH. (2014). De-Noising Model for Weberface-Based and Max-Filter-Based Illumination Invariant Face Recognition. In: Jeong, YS., Park, YH., Hsu, CH., Park, J. (eds) Ubiquitous Information Technologies and Applications. Lecture Notes in Electrical Engineering, vol 280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41671-2_47

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  • DOI: https://doi.org/10.1007/978-3-642-41671-2_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41670-5

  • Online ISBN: 978-3-642-41671-2

  • eBook Packages: EngineeringEngineering (R0)

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