Biometric retina identification based on neural network

被引:32
|
作者
Sadikoglu, Fahreddin [1 ]
Uzelaltinbulat, Selin [2 ]
机构
[1] Near East Univ, Dept Elect & Elect Engn, POB 99138, TR-10 North Cyprus, Mersin, Turkey
[2] Near East Univ, Dept Comp Engn, POB 99138, TR-10 North Cyprus, Mersin, Turkey
关键词
Neural network; retina recognition; backpropagation algorithm; SEGMENTATION;
D O I
10.1016/j.procs.2016.09.365
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 the design of recognition system for retinal images using neural network is considered. Retina based recognition is perceived as the most secure method for identification of an identity used to distinguish individuals. The retina recognition stages including retina image acquisition, feature extraction and classification of the features are discussed. The structure of the neural network based retina identification is presented. Training of neural network based recognition system is performed using backpropagation algorithm. The structure of neural networks used for retina recognition and its learning algorithm are described. The implementation of recognition system has been done using MATLAB package. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:26 / 33
页数:8
相关论文
共 50 条
  • [31] Using a Probabilistic Neural Network for lip-based biometric verification
    Wrobel, Krzysztof
    Doroz, Rafal
    Porwik, Piotr
    Naruniec, Jacek
    Kowalski, Marek
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2017, 64 : 112 - 127
  • [32] Network Traffic Identification Algorithm Based on Neural Network
    Wu, Fei
    Ye, Yong
    Li, Hongfa
    Ni, Shilong
    Su, Jiangwen
    INTERNATIONAL JOURNAL OF FUTURE GENERATION COMMUNICATION AND NETWORKING, 2016, 9 (12): : 129 - 138
  • [33] Autoencoder Neural Networks for Outlier Correction in ECG-Based Biometric Identification
    Karpinski, Mikolaj
    Khoma, Volodymyr
    Dudykevych, Valerii
    Khoma, Yuriy
    Sabodashko, Dmytro
    PROCEEDINGS OF THE 2018 IEEE 4TH INTERNATIONAL SYMPOSIUM ON WIRELESS SYSTEMS WITHIN THE INTERNATIONAL CONFERENCES ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS (IDAACS-SWS), 2018, : 210 - 215
  • [34] Compatibility of biometric strengthening with probabilistic neural network
    Ooi, Shih-Yin
    Teoh, Andrew Beng Jin
    Ong, Thian-Song
    2008 INTERNATIONAL SYMPOSIUM ON BIOMETRICS AND SECURITY TECHNOLOGIES, 2008, : 88 - +
  • [35] Biometric entropy of retina
    Semerad, Lukas
    Drahansky, Martin
    2015 INTERNATIONAL CONFERENCE ON INFORMATION AND DIGITAL TECHNOLOGIES (IDT), 2015, : 302 - 304
  • [36] Study on a Biometric Authentication Model based on ECG using a Fuzzy Neural Network
    Kim, Ho J.
    Lim, Joon S.
    4TH INTERNATIONAL CONFERENCE ON ADVANCED ENGINEERING AND TECHNOLOGY (4TH ICAET), 2018, 317
  • [37] Iris-based Biometric Recognition using Modified Convolutional Neural Network
    Thuong Le-Tien
    Hanh Phan-Xuan
    Phu Nguyen-Duy
    Loc Le-Ba
    2018 INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR COMMUNICATIONS (ATC), 2018, : 184 - 188
  • [38] An Adaptive Biometric System Based on Palm Texture Feature and LVQ Neural Network
    Ouyang, Chen-Sen
    Ju, Ming-Yi
    Yang, Han-Lin
    OPPORTUNITIES AND CHALLENGES FOR NEXT-GENERATION APPLIED INTELLIGENCE, 2009, 214 : 25 - +
  • [39] Frequency spectrograms for biometric keystroke authentication using neural network based classifier
    Alpar, Orcan
    KNOWLEDGE-BASED SYSTEMS, 2017, 116 : 163 - 171
  • [40] A Non-Contact PPG Biometric System Based on Deep Neural Network
    Patil, Omkar R.
    Wang, Wei
    Gao, Yang
    Xu, Wenyao
    Jin, Zhanpeng
    2018 IEEE 9TH INTERNATIONAL CONFERENCE ON BIOMETRICS THEORY, APPLICATIONS AND SYSTEMS (BTAS), 2018,