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Chinese Conference on Biometric Recognition

CCBR 2016: Biometric Recognition pp 195–202Cite as

Interval Type-2 Fuzzy Linear Discriminant Analysis for Gender Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9967))

Abstract

In this paper, we propose the interval type-2 fuzzy linear discriminant analysis (IT2FLDA) algorithm for gender recognition. In this algorithm, we first proposed the supervised interval type-2 fuzzy C-Mean (IT2FCM), which introduces the classified information to the IT2FCM, and then the supervised IT2FCM is incorporated into traditional linear discriminant analysis (LDA). By this way, means of each class that are estimated by the supervised IT2FCM can converge to a more desirable location than means of each class obtained by class sample average and the type-1 fuzzy k-nearest neighbor (FKNN) method in the presence of noise. Furthermore, the IT2FLDA is able to minimize the effects of uncertainties, find the optimal projective directions and make the feature subspace discriminating and robust, which inherits the benefits of the supervised IT2FCM and traditional LDA. The experimental results show that the IT2FLDA improved the gender recognition rate when compared to the results from the previous techniques.

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Acknowledgments

This work was supported by the National Key Science & Technology Pillar Program of China (No.2014BAG01B03), the National Natural Science Foundation of China (No. 61374194 & No. 61403081), the Natural Science Foundation of Jiangsu Province (No. BK20140638), Scientific Research Foundation of Graduate School of Southeast University (YBJJ1519) and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. School of Automation, Southeast University, Nanjing, 210096, China

    Yijun Du, Xiaobo Lu & Changhui Hu

  2. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Nanjing, 210096, China

    Yijun Du, Xiaobo Lu & Changhui Hu

  3. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, 210096, China

    Weili Zeng

Authors
  1. Yijun Du
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  2. Xiaobo Lu
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  3. Weili Zeng
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  4. Changhui Hu
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Corresponding author

Correspondence to Xiaobo Lu .

Editor information

Editors and Affiliations

  1. Sichuan University , Chengdu, China

    Zhisheng You

  2. Tsinghua University , Beijing, China

    Jie Zhou

  3. Beihang University , Beijing, China

    Yunhong Wang

  4. Chinese Academy of Sciences , Beijing, China

    Zhenan Sun

  5. Chinese Academy of Sciences , Beijing, China

    Shiguang Shan

  6. Sun Yat-sen University , Guangzhou, China

    Weishi Zheng

  7. Tsinghua University , Beijing, China

    Jianjiang Feng

  8. Sichuan University , Chengdu, China

    Qijun Zhao

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Du, Y., Lu, X., Zeng, W., Hu, C. (2016). Interval Type-2 Fuzzy Linear Discriminant Analysis for Gender Recognition. In: You, Z., et al. Biometric Recognition. CCBR 2016. Lecture Notes in Computer Science(), vol 9967. Springer, Cham. https://doi.org/10.1007/978-3-319-46654-5_22

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  • DOI: https://doi.org/10.1007/978-3-319-46654-5_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46653-8

  • Online ISBN: 978-3-319-46654-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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