Color Two-Dimensional Principal Component Analysis for Face Recognition Based on Quaternion Model

被引：22
|
作者：
Jia, Zhi-Gang [1 ]
Ling, Si-Tao [2 ]
Zhao, Mei-Xiang [1 ,3 ]
机构：
[1] Jiangsu Normal Univ, Sch Math & Stat, Jiangsu Key Lab Educ Big Data Sci & Engn, Xuzhou 221116, Jiangsu, Peoples R China
[2] China Univ Min & Technol, Sch Math, Xuzhou 221116, Jiangsu, Peoples R China
[3] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Jiangsu, Peoples R China
来源：
INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2017, PT I | 2017年 / 10361卷
基金：
中国国家自然科学基金;
关键词：
Color face recognition; Eigenface; Quaternion matrix; Color; 2DPCA; PCA; EIGENFACES;
D O I：
10.1007/978-3-319-63309-1_17
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The color two-dimensional principal component analysis (color 2DPCA) approach based on quaternion model is presented for color face recognition. Based on 2D quaternion matrices rather than 1D quaternion vectors, color 2DPCA combines the color information and the spatial characteristic for face recognition, and straightly computes the low-dimensional covariance matrix of the training color face images and determines the corresponding eigenvectors in a short CPU time. The image reconstruction theory is also built on color 2DPCA. The experiments on real face data sets are provided to validate the feasibility and effectiveness of the proposed algorithm.
引用
收藏
页码：177 / 189
页数：13
相关论文
共 50 条
  • [1] Symmetry based two-dimensional principal component analysis for face recognition
    Ding, Mingyong
    Lu, Congde
    Lin, Yunsong
    Tong, Ling
    [J]. ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 2, PROCEEDINGS, 2007, 4492 : 1048 - +
  • [2] Face recognition with DWT and two-dimensional principal component analysis
    Yin Hongtao
    Fu Ping
    Meng Shengwei
    [J]. ICEMI 2007: PROCEEDINGS OF 2007 8TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL I, 2007, : 86 - 89
  • [3] Improved Two-Dimensional Quaternion Principal Component Analysis
    Zhao, Meixiang
    Jia, Zhigang
    Gong, Dunwei
    [J]. IEEE ACCESS, 2019, 7 : 79409 - 79417
  • [4] Probabilistic two-dimensional principal component analysis and its mixture model for face recognition
    Wang, Haixian
    Chen, Sibao
    Hu, Zilan
    Luo, Bin
    [J]. NEURAL COMPUTING & APPLICATIONS, 2008, 17 (5-6): : 541 - 547
  • [5] Probabilistic two-dimensional principal component analysis and its mixture model for face recognition
    Haixian Wang
    Sibao Chen
    Zilan Hu
    Bin Luo
    [J]. Neural Computing and Applications, 2008, 17 : 541 - 547
  • [6] AN IMPROVED FRACTIONAL TWO-DIMENSIONAL PRINCIPAL COMPONENT ANALYSIS FOR FACE RECOGNITION
    Alsaqre, Falah
    [J]. JORDANIAN JOURNAL OF COMPUTERS AND INFORMATION TECHNOLOGY, 2022, 8 (01): : 87 - 97
  • [7] Application of two-dimensional principal component analysis for recognition of face images
    Shchegoleva N.L.
    Kukharev G.A.
    [J]. Pattern Recognition and Image Analysis, 2010, 20 (4) : 513 - 527
  • [8] Advanced variations of two-dimensional principal component analysis for face recognition
    Zhao, Meixiang
    Jia, Zhigang
    Cai, Yunfeng
    Chen, Xiao
    Gong, Dunwei
    [J]. NEUROCOMPUTING, 2021, 452 : 653 - 664
  • [9] Face recognition using two-dimensional nonnegative principal component analysis
    Ma, Peng
    Yang, Dan
    Ge, Yongxin
    Zhang, Xiaohong
    Qu, Ying
    [J]. JOURNAL OF ELECTRONIC IMAGING, 2012, 21 (03)
  • [10] Fuzzy Kernel Two-Dimensional Principal Component Analysis for Face Recognition
    Zeng, J. X.
    Chen, P.
    Tian, J. Q.
    Fu, X.
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRIAL ENGINEERING (AIIE 2015), 2015, 123 : 357 - 360
12345