Dorsal Hand Vein Pattern Recognition Using Statistical Features and Artificial Neural Networks

被引:0
|
作者
Chin, Sze Wei [1 ]
Tay, Kim Gaik [2 ]
Huong, Audrey [2 ]
Chew, Chang Choon [2 ]
机构
[1] UTHM, Elect Engn Dept, Batu Pahat, Malaysia
[2] Univ Tun Hussein Onn Malaysia, Fac Elect & Elect Engn, Batu Pahat, Malaysia
关键词
Biometric; dorsal hand vein; statistical features; GLCM; ANN;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Even though various dorsal hand vein pattern extraction techniques have been proposed for biometric identification, there remains considerable room for performance. This paper describes dorsal hand vein recognition using statistical and Gray Level Co-occurrence Matrix (GLCM) based features extraction techniques and artificial neural networks (ANN). For this purpose, 240 images of 80 users were obtained from Bosphorus Hand Vein Database. The images were first pre-processed by cropping region of interest (ROI), before the application of mean filtering, contrast enhancing and histogram equalizing. The ROI was then segmented by implementation of binarization method. The statistical and GLCM features were then extracted from the segmented ROI. These extracted features were sent to ANN for classification of the images. The training result shows that the proposed technique is able to recognize dorsal hand vein pattern with with considerably high accuracy of 9932%.
引用
收藏
页码:217 / 221
页数:5
相关论文
共 50 条
  • [1] Dorsal Hand Vein Recognition Based On Convolutional Neural Networks
    Wan, Haipeng
    Chen, Lei
    Song, Hong
    Yang, Jian
    2017 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2017, : 1215 - 1221
  • [2] DORSAL HAND VEIN PATTERN RECOGNITION SYSTEM BASED ON NEURAL NETWORK
    Bhosale, Aishwarya S.
    Jadhav, Maruti R.
    2017 INTERNATIONAL CONFERENCE OF ELECTRONICS, COMMUNICATION AND AEROSPACE TECHNOLOGY (ICECA), VOL 2, 2017, : 52 - 55
  • [3] Dorsal Hand Vein Pattern Analysis and Neural Networks for Biometric Authentication
    Belean, Bogdan
    Streza, Mihaela
    Crisan, Septimiu
    Emerich, Simina
    STUDIES IN INFORMATICS AND CONTROL, 2017, 26 (03): : 305 - 314
  • [4] Gaussian directional pattern for dorsal hand vein recognition
    Hsu, C. -B.
    Lee, J. -C.
    Chuang, S. -J.
    Kuei, P. -Y.
    IMAGING SCIENCE JOURNAL, 2015, 63 (01): : 54 - 62
  • [5] Special issue on artificial neural networks and statistical pattern recognition
    Jain, AK
    Mao, JC
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 1997, 8 (01): : 1 - 4
  • [6] A Comparative Study of Signature Recognition Problem Using Statistical Features and Artificial Neural Networks
    Akram, Mahabub
    Qasim, Romasa
    Amin, M. Ashraful
    2012 INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV), 2012, : 925 - 929
  • [7] PATTERN-RECOGNITION USING ARTIFICIAL NEURAL NETWORKS
    MAH, RSH
    CHAKRAVARTHY, V
    COMPUTERS & CHEMICAL ENGINEERING, 1992, 16 (04) : 371 - 377
  • [8] Artificial neural networks for pattern recognition
    Corne, SA
    CONCEPTS IN MAGNETIC RESONANCE, 1996, 8 (05): : 303 - 324
  • [9] Fusion of Partition Local Binary Patterns and Convolutional Neural Networks for Dorsal Hand Vein Recognition
    Li, Kefeng
    Liu, Quankai
    Zhang, Guangyuan
    BIOMETRIC RECOGNITION (CCBR 2021), 2021, 12878 : 177 - 184
  • [10] Automatic recognition of machining features using artificial neural networks
    V. B. Sunil
    S. S. Pande
    The International Journal of Advanced Manufacturing Technology, 2009, 41 : 932 - 947