Palmprint recognition: Two level structure matching

被引:0
|
作者
Pradeep, Nalin [1 ]
Jain, Mayur D. [2 ]
Prakash, C. [1 ]
Raman, Balasubramanian [3 ]
机构
[1] Sarnoff Innovat Technol, Vis Grp, Bangalore, Karnataka, India
[2] Microsoft R&D India Pvt Ltd, Hyderabad, Andhra Pradesh, India
[3] Indian Inst Technol, Roorkee, Uttar Pradesh, India
关键词
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
We introduce palmprint recognition, one of the most reliable personal identification methods in the biometric technology. In this paper, a new approach to the palmprint matching by constructing local and global line feature structures is presented. The datum point of palmprint acts as an important registration due to its remarkable advantage about its spatial location. Initially we define all possible local line feature structures constructed with adjacent lines, around datum point. Through a first level match using these local line feature structures, we get best matched line features. Using these best matched line features, we construct a global line feature structure of palmprint with datum point as reference. This global line feature structure is spread across in four quadrants, datum point being the origin. We then carry out a second level match using this global structure of palmprint to reliably determine its uniqueness. The two levels of matching using local and global line feature structures helps in effective palmprint recognition. With several palmprint images, we tested out proposed verification system and the experimental result shows that the performance of our algorithm is good.
引用
收藏
页码:664 / +
页数:2
相关论文
共 50 条
  • [1] Matching Score Level Fusion for Face and Palmprint Recognition System on Spatial Domain
    Rahmi, Zulaida
    Ahmad, Muhammad Imran
    Isa, Mohd Nazrin Md
    Khalib, Zahereel Ishwar Abdul
    2019 IEEE 9TH INTERNATIONAL CONFERENCE ON SYSTEM ENGINEERING AND TECHNOLOGY (ICSET), 2019, : 45 - 49
  • [2] A two-level matching scheme for speedy and accurate palmprint identification
    Li, Fang
    Leung, Maylor K. H.
    Yu, Xiaozhou
    ADVANCES IN MULTIMEDIA MODELING, PT 2, 2007, 4352 : 323 - +
  • [3] Palmprint Recognition using Robust Template Matching
    Poonia, Poonam
    Ajmera, Pawan K.
    Shende, Vijayendra
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE, 2020, 167 : 727 - 736
  • [4] 2.5D Palmprint Recognition using Signal level Fusion and Graph based Matching
    Gangapure, Vijay N.
    Sarkar, Rahul
    Chowdhury, Ananda S.
    2017 NINTH INTERNATIONAL CONFERENCE ON ADVANCES IN PATTERN RECOGNITION (ICAPR), 2017, : 263 - 268
  • [5] Wavelet Energy Feature Extraction and Matching for Palmprint Recognition
    Xiang-Qian Wu
    Kuan-Quan Wang
    David Zhang
    Journal of Computer Science and Technology, 2005, 20 : 411 - 418
  • [6] Palmprint recognition based on directional features and graph matching
    Han, Yufei
    Tan, Tieniu
    Sun, Zhenan
    ADVANCES IN BIOMETRICS, PROCEEDINGS, 2007, 4642 : 1164 - +
  • [7] Wavelet energy feature extraction and matching for palmprint recognition
    Wu, XQ
    Wang, KQ
    Zhang, D
    JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2005, 20 (03) : 411 - 418
  • [8] Palmprint Recognition using Rank Level Fusion
    Kumar, Ajay
    Shekhar, Sumit
    2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, : 3121 - 3124
  • [9] Matching Similarity Scores for a Minutiae-based Palmprint Recognition
    Faisal, Touka
    Benatchba, Karima
    Koudil, Mouloud
    45TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2019), 2019, : 132 - 137
  • [10] Palmprint recognition method based on score level fusion
    Zhang, Shuwen
    Gu, Xuxin
    OPTIK, 2013, 124 (18): : 3340 - 3344