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Two-dimensional discriminant locality preserving projections (2DDLPP) and its application to feature extraction via fuzzy set

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Abstract

This paper presents a new method for image feature extraction, namely, the fuzzy 2D discriminant locality preserving projections (F2DDLPP) based on the 2D discriminant locality preserving projections (2DDLPP) and fuzzy set theory. Firstly, we calculate the membership degree matrix by fuzzy k-nearest neighbor (FKNN), then we incorporate the membership degree matrix into the definition of the intra-class scatter matrix and inter-class scatter matrix, respectively. Secondly, we can get the fuzzy intra-class scatter matrix and fuzzy inter-class scatter matrix, respectively. The FKNN is implemented to achieve the distribution information of original samples, and this information is utilized to redefine corresponding scatter matrices. So, F2DDLPP can extract discriminative features from overlapping (outlier) samples which is different to the conventional 2DDLPP. Finally, Experiments on the Yale, ORL face databases, USPS database and PolyU palmprint database are demonstrated to verify the effectiveness of the proposed algorithm.

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Acknowledgments

This work is partially supported by the National Science Foundation of China under grant no. 61462064, 61203243, 61272077, 61202319, 61403188, 61563037, the China Postdoctoral Science Foundation under grant No. 2014 T70453, 2013 M530223 and Jiangsu Provincial Postdoctoral Science Foundation under grant No.1301095C, the Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information (Nanjing University of Science and Technology), Ministry of Education (Grant No. 30920140122006), the University Natural Science Fund of JiangSu Province, China (Grant No.15KJB520018).

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Authors and Affiliations

  1. School of Technology, Nanjing Audit University, Nanjing, 211815, China

    Minghua Wan, Guowei Yang, Shan Gai & Zhangjing Yang

  2. Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, Nanjing University of Science and Technology, Nanjing, 210094, China

    Minghua Wan

  3. Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, 211171, People’s Republic of China

    Minghua Wan

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  1. Minghua Wan
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  2. Guowei Yang
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Correspondence to Minghua Wan.

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Wan, M., Yang, G., Gai, S. et al. Two-dimensional discriminant locality preserving projections (2DDLPP) and its application to feature extraction via fuzzy set. Multimed Tools Appl 76, 355–371 (2017). https://doi.org/10.1007/s11042-015-3057-8

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  • DOI: https://doi.org/10.1007/s11042-015-3057-8

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