Face recognition based on improved Euclid norm

被引:0
|
作者
Cao, WM [1 ]
Yuan, Y [1 ]
Cai, WW [1 ]
Wang, SJ [1 ]
机构
[1] Zhejiang Univ Technol, Hangzhou 310032, Peoples R China
来源
2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3 | 2004年
关键词
euclid nonn; face recognition; principal component algorithin;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a new face recognition algorithm based on improved Euclid norm. The method, compared with conventional algorithm, has all improved recognition rate for face images with large variation in lighting direction. Testing our system on Yale face database, the recognition rate is 98.8%. which proves the face recognition algorithm is efficient.
引用
收藏
页码:934 / 937
页数:4
相关论文
共 50 条
  • [11] PCA Based Improved Face Recognition System
    Dharejo, Fayaz Ali
    Jatoi, Munsif Ali
    Hao, Zongbo
    Tunio, Majid Ali
    INFORMATION TECHNOLOGY AND INTELLIGENT TRANSPORTATION SYSTEMS (ITITS 2017), 2017, 296 : 429 - 440
  • [12] Face recognition based on improved LBP algorithm
    Shi, Zhi-Yuan
    Lin, Mei-Jia
    Gao, Zhi-Bin
    Wu, Yan-Yang
    Zhang, Hao
    Li, Li-Zhong
    Journal of Computers (Taiwan), 2019, 30 (04) : 122 - 129
  • [13] Face recognition based on improved SIFT features
    Liao, B., 1600, Asian Network for Scientific Information (12):
  • [14] Face Recognition Method Based on Improved LDA
    Yuan Wei
    2017 NINTH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC 2017), VOL 2, 2017, : 456 - 459
  • [15] Face recognition research based on improved PCA and improved LDA
    Gan, Junying
    Shao, Pan
    Xiao, Juan
    Journal of Information and Computational Science, 2010, 7 (12): : 2513 - 2520
  • [16] Enhanced nuclear norm based matrix regression for occluded face recognition
    Li, Qin
    He, Huihui
    Lai, Hong
    Cai, Tie
    Wang, Qianqian
    Gao, QuanXue
    PATTERN RECOGNITION, 2022, 126
  • [17] Fisher discrimination-based -norm sparse representation for face recognition
    Zhao, Lu
    Zhang, Yong
    Yin, Baocai
    Sun, Yanfeng
    Hu, Yongli
    Piao, Xinglin
    Wu, Qianjun
    VISUAL COMPUTER, 2016, 32 (09): : 1165 - 1178
  • [18] FACE RECOGNITION BASED ON FLDA, CPCA AND IMPROVED HMM
    Zhang, Qiang
    Zhou, Changjun
    Zhao, Jing
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2010, 6 (02): : 801 - 807
  • [19] FACE RECOGNITION BASED ON IMPROVED SUPPORT VECTOR CLUSTERING
    Wang, Yongqing
    Liu, Xiling
    INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS, 2014, 7 (04): : 1807 - 1829
  • [20] LBPH Based Improved Face Recognition At Low Resolution
    Ahmed, Aftab
    Guo, Jiandong
    Ali, Fayaz
    Deeba, Farha
    Ahmed, Awais
    2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND BIG DATA (ICAIBD), 2018, : 144 - 147