Banknote Image Defect Recognition Method Based on Convolution Neural Network

被引：10
|
作者：
Wang Ke [1 ,2 ]
Wang Huiqin [1 ,2 ]
Shu Yue [3 ]
Mao Li [2 ]
Qiu Fengyan [4 ,5 ]
机构：
[1] Xian Univ Architecture & Technol, Sch Management, Xian 710055, Peoples R China
[2] Xian Univ Architecture & Technol, Sch Informat & Control Engineer, Xian 710055, Peoples R China
[3] Chengdu Banknote Printing Ltd, Chengdu 611103, Peoples R China
[4] Peoples Bank China, Business Dept, Xian Branch, Xian 710002, Peoples R China
[5] Peoples Bank China, Dept Management, Xian Branch, Xian 710002, Peoples R China
来源：
INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS | 2016年 / 10卷 / 06期
关键词：
Convolution Neural Network; Defect Recognition; Banknote Image; Deep-learning;
D O I：
10.14257/ijsia.2016.10.6.26
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
There are shortcomings in the currently used traditional CCD imaging system which can automatically recognize banknote image defect, such as the need to manually extract the defect characteristics and low accuracy rate of detection results. This paper briefly introduced the advantage of convolution Neural Network (CNN) in image classification and designed a image defect identification method based on convolutional neural network (CNN). The experimental results on data sets show that the identification accuracy rate of this method is 95.6%, which is significantly better than traditional identification method.
引用
收藏
页码：269 / 279
页数：11
相关论文
共 50 条
  • [21] An Automatic Target Recognition Algorithm for SAR Image Based on Improved Convolution Neural Network
    Qiao Weilei
    Zhang Xinggan
    Fen Ge
    PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2017, : 551 - 555
  • [22] Tractor driver fatigue detection based on convolution neural network and facial image recognition
    Lu W.
    Hu H.
    Wang J.
    Wang L.
    Deng Y.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2018, 34 (07): : 192 - 199
  • [23] Image Classification Based on Image Hash Convolution Neural Network
    Chen, Yaoxing
    Yan, Yunyi
    Zhao, Dan
    INTELLIGENT DATA ANALYSIS AND APPLICATIONS, (ECC 2016), 2017, 535 : 61 - 68
  • [24] A Convolution Neural Network Engine for Sclera Recognition
    Maheshan, M. S.
    Harish, B. S.
    Nagadarshan, N.
    INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2020, 6 (01): : 78 - 83
  • [25] Bimanual gesture recognition based on convolution neural network
    Wu H.
    Li G.
    Sun Y.
    Jiang G.
    Jiang D.
    International Journal of Wireless and Mobile Computing, 2020, 18 (04) : 311 - 319
  • [26] Vehicle recognition using convolution neural network
    Khan, Maleika Heenaye-Mamode
    Khan, Chonnoo Abubakar Siddick
    Oumeir, Rengony Mohammad
    INTERNATIONAL JOURNAL OF BIOMETRICS, 2023, 15 (3-4) : 344 - 358
  • [27] Emotion Recognition Algorithm Based on Convolution Neural Network
    Cheng, Chunling
    Wei, Xianwei
    Jian, Zhou
    2017 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (IEEE ISKE), 2017,
  • [28] Buckwheat Disease Recognition Based on Convolution Neural Network
    Liu, Xiaojuan
    Zhou, Shangbo
    Chen, Shanxiong
    Yi, Zelin
    Pan, Hongyu
    Yao, Rui
    APPLIED SCIENCES-BASEL, 2022, 12 (09):
  • [29] Facial Expression Recognition Based on Convolution Neural Network
    Duan, Yue
    Zhou, Linli
    Wu, Yue
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING, INFORMATION SCIENCE & APPLICATION TECHNOLOGY (ICCIA 2017), 2017, 74 : 339 - 343
  • [30] X-ray image defect recognition method for pipe weld based on improved convolutional neural network
    Fan D.
    Hu A.
    Huang J.
    Xu Z.
    Xu X.
    Hanjie Xuebao/Transactions of the China Welding Institution, 2020, 41 (01): : 7 - 11
12345