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Quaternion Based Maximum Margin Criterion Method for Color Face Recognition

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Abstract

Color is one of the basic features of images, which can provide very useful information and play an important role in face recognition. By using the quaternion matrix representation, the R, G, B information of each pixel is not destroyed and it can be taken as a organic body. Therefore, this paper proposes a quaternion based maximum margin criterion (QMMC) algorithm. Firstly, the quaternion number is used to denote the pixel of the color image, and a quaternion vector is taken to represent the color image. Secondly, the maximum margin criterion algorithm is used to project the quaternion vector in the high-dimension space into a low-dimension space. Finally, the nearest neighbor classification are taken for classification recognition. Numerous experiments show that the proposed QMMC can achieve better recognition performance.

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Acknowledgments

This work was partly supported by NSFC of China (U1504610, 61402274, 61672333), the Natural Science Foundations of Henan Province (14A413013, 142102210584, 13B520992), the Natural Science Foundations of Luoyang (1401036A), The Development Foundations of Henan University of Science and Technology (2014ZCX013), the Key Science and Technology Program of Shaanxi Province (No.2016GY-081).

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Authors and Affiliations

  1. Information Engineering College, Henan University of Science and Technology, Luoyang, China

    Zhonghua Liu, Yong Qiu & Jiexin Pu

  2. School of Computer Science, Shaanxi Normal University, Xi’an, China

    Yali Peng

  3. Xihua University, Chengdu, China

    Xiaoli Zhang

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  1. Zhonghua Liu
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  2. Yong Qiu
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  3. Yali Peng
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  4. Jiexin Pu
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  5. Xiaoli Zhang
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Correspondence to Yali Peng.

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Liu, Z., Qiu, Y., Peng, Y. et al. Quaternion Based Maximum Margin Criterion Method for Color Face Recognition. Neural Process Lett 45, 913–923 (2017). https://doi.org/10.1007/s11063-016-9550-x

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