Aspects of Iris Image and Iris Match Pair Quality

被引：0
|
作者：
Flynn, Patrick J. [1 ]
Bowyer, Kevin W. [1 ]
机构：
[1] Univ Notre Dame, Dept Comp Sci & Eng, Notre Dame, IN 46556 USA
来源：
BIOMETRIC TECHNOLOGY FOR HUMAN IDENTIFICATION VII | 2010年 / 7667卷
关键词：
Iris recognition; image quality; database; sensors; demographics;
D O I：
10.1117/12.855708
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Iris recognition technology has the potential to broaden to include non-ideal imaging situations, as well as scale to national-level deployments. Hence, the study of population factors, subject intrinsics, and sensing contexts that can individually or collectively impact iris recognition performance assumes increased importance. This presentation summarizes recent research on a number of such "quality variables" and motivates the need for large data sets exhibiting a variety of such non-idealities to adequately characterize performance.
引用
收藏
页数：5
相关论文
共 50 条
  • [1] Learning to Predict Match Scores for Iris Image Quality Assessment
    Happold, Michael
    [J]. 2014 IEEE/IAPR INTERNATIONAL JOINT CONFERENCE ON BIOMETRICS (IJCB 2014), 2014,
  • [2] COMPREHENSIVE ASSESSMENT OF IRIS IMAGE QUALITY
    Li, Xingguang
    Sun, Zhenan
    Tan, Tieniu
    [J]. 2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2011,
  • [3] Image quality assessment for iris biometric
    Kalka, Nathan D.
    Zuo, Jinyu
    Schmid, Natalia A.
    Cukic, Bojan
    [J]. BIOMETRIC TECHNOLOGY FOR HUMAN IDENTIFICATION III, 2006, 6202
  • [4] Quality Evaluation of the Sequence Iris Image
    Zhou, Yanhua
    Cao, Liuyang
    Yan, Fei
    Tian, Yantao
    [J]. 2014 FOURTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC), 2014, : 809 - 814
  • [5] The algorithm of iris image quality evaluation
    Pan, Lili
    Xie, Mei
    [J]. 2007 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS PROCEEDINGS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS; VOL 2: SIGNAL PROCESSING, COMPUTATIONAL INTELLIGENCE, CIRCUITS AND SYSTEMS, 2007, : 616 - +
  • [6] The study of iris image quality assessment
    Li, Q
    Jiang, CJ
    Niu, XM
    Sun, SH
    [J]. ISTM/2005: 6TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-9, CONFERENCE PROCEEDINGS, 2005, : 6320 - 6323
  • [7] ENHANCED IRIS RECOGNITION BASED ON IMAGE MATCH AND HAMMING DISTANCE
    Gao Xiaoxing
    Feng Sumin
    Cui Han
    [J]. INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS, 2015, 8 (02): : 1085 - 1103
  • [8] Video Iris Recognition Based on Iris Image Quality Evaluation and Semantic Classification
    Garea-Llano, Eduardo
    Morales-Gonzalez, Annette
    Osorio-Roig, Daile
    [J]. PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS (CIARP 2019), 2019, 11896 : 198 - 208
  • [9] Iris Image Quality Assessment Based on Quality Parameters
    Makinana, Sisanda
    Malumedzha, Tendani
    Nelwamondo, Fulufhelo V.
    [J]. INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT 1, 2014, 8397 : 571 - 580
  • [10] The research on adaptive fast iris capture and online iris image quality assessment algorithm
    Peng, Zhiyong
    Wu, Jun
    [J]. OPTIK, 2015, 126 (24): : 5971 - 5978
12345