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Towards a face recognition method based on uncorrelated discriminant sparse preserving projection

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Abstract

Feature extraction has always been an important step in face recognition, the quality of which directly determines recognition result. Based on making full use of advantages of Sparse Preserving Projection (SPP) on feature extraction, the discriminant information was introduced into SPP to arrive at a novel supervised feather extraction method that named Uncorrelated Discriminant SPP (UDSPP) algorithm. The obtained projection with the method by sparse preserving intra-class and maximizing distance inter-class can effectively express discriminant information, while preserving local neighbor relationship. Moreover, statistics uncorrelated constraint was also added to decrease redundancy among feature vectors so as to obtain more information as possible with little vectors as possible. The experimental results show that the recognition rate improved compared with SPP. The method is also superior to recognition methods based on Euclidean distance in processing face database in light.

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Acknowledgments

The research was founded within the project No. 132102210575 entitled: “Research on image fusion technology based on Representation Learning”, being a key scientific and technical tackle-key-problem plan project of Henan province, supported by The Science and Technology Department of Henan Province, China.

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Authors and Affiliations

  1. School of Computer Science and Technology, Zhoukou Normal University, Zhoukou, 466001, China

    Zhanwei Chen

  2. School of Computer and Communication Engineering, Light Engineering Institutes of Zhengzhou, Zhengzhou, 450002, China

    Wei Huang

  3. SIAT, Chinese Academy of Science, Beijing, China

    Zhihan Lv

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  1. Zhanwei Chen
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  2. Wei Huang
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  3. Zhihan Lv
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Correspondence to Zhihan Lv.

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Chen, Z., Huang, W. & Lv, Z. Towards a face recognition method based on uncorrelated discriminant sparse preserving projection. Multimed Tools Appl 76, 17669–17683 (2017). https://doi.org/10.1007/s11042-015-2882-0

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  • DOI: https://doi.org/10.1007/s11042-015-2882-0

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