IRIS DETECTION AND RECOGNITION USING 2 FOLD TECHNIQUE

被引:0
|
作者
Vishwakarma, Dinesh Kumar [1 ]
Jain, Divyansh [2 ]
Rajora, Shantanu [3 ]
机构
[1] Delhi Technol Univ, Dept Elect & Commun Engn, Delhi, India
[2] Delhi Technol Univ, Dept Elect Engn, Delhi, India
[3] Delhi Technol Univ, Dept Comp Sci & Engn, Delhi, India
来源
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA) | 2017年
关键词
Computer Vision; Pattern Recognition; Biometrics;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The objective of this paper is to introduce a new integrated methodology for iris detection and recognition using a two fold method to deduce better results as compared to the existing techniques. The methodology primarily employs the Finite Impulse Response(FIR) and Gabor wavelet transform as for computing fundamentals. The figurative classification in the proposed algorithm is on the basis of euclidean distance. Thus the proposed algorithm solely works on construing the euclidean distances of the test sample with respect to that of the samples in the data set in the either fold procedures. Further the least euclidean distance measured is considered as the perfect match for the input test sample. As a result of extensive testing and implementation of the proposed algorithm/methodology in this paper, satisfactory accuracy and results are obtained as tested on Self Generated Dataset. The proposed algorithm focus on extensively using all the data available and retrievable from the human iris, specifically the red, green and blue segments, i.e RGB scheme unlike traditional iris based recognition wiz. computation on grayscale inputs, thus on the contrary, the methodology presented in this paper employs suitable color coding pattern using FIR(Finite Impulse Response) in addition to the Gabor filter texture classification technique.
引用
收藏
页码:1046 / 1051
页数:6
相关论文
共 50 条
  • [31] Iris recognition using class-specific dictionaries
    Naseem, Imran
    Aleem, Affan
    Togneri, Roberto
    Bennamoun, Mohammed
    COMPUTERS & ELECTRICAL ENGINEERING, 2017, 62 : 178 - 193
  • [32] Providing Reliability Using Potent Features of Iris Recognition
    Pathak, Shreyas
    Zafar, Sameena
    2014 2ND INTERNATIONAL CONFERENCE ON DEVICES, CIRCUITS AND SYSTEMS (ICDCS), 2014,
  • [33] Iris recognition using multi-resolution transforms
    Arivazhagan, S.
    Ganesan, L.
    Srividya, T.
    INTERNATIONAL JOURNAL OF BIOMETRICS, 2009, 1 (03) : 254 - 267
  • [34] Iris recognition system using deep learning techniques
    Sallam, Amer A.
    Amery, Hadeel
    Saeed, Ahmed Y. A.
    INTERNATIONAL JOURNAL OF BIOMETRICS, 2023, 15 (06) : 705 - 725
  • [35] Analysis of Multimodal Biometric Recognition Using Iris and Sclera
    Guliani, Neha
    Shukla, Manoj Kumar
    Dubey, Ashwani Kumar
    Jaffery, Zainul Abdin
    2017 6TH INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (TRENDS AND FUTURE DIRECTIONS) (ICRITO), 2017, : 472 - 475
  • [36] Using Iris Recognition to Secure Medical Images on the Cloud
    Sabri, Heba M.
    Elkhameesy, Nashaat
    Hefny, Hesham A.
    PROCEEDINGS OF 2015 THIRD IEEE WORLD CONFERENCE ON COMPLEX SYSTEMS (WCCS), 2015,
  • [37] Iris Recognition Using Gabor Filters and the Fractal Dimension
    Tsai, C. C.
    Taur, J. S.
    Tao, C. W.
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2009, 25 (02) : 633 - 647
  • [38] Presentation Attack Detection for Mobile Device-Based Iris Recognition
    Bartuzi, Ewelina
    Trokielewicz, Mateusz
    IMAGE PROCESSING AND COMMUNICATIONS: TECHNIQUES, ALGORITHMS AND APPLICATIONS, 2020, 1062 : 30 - 40
  • [39] Presentation Attack Detection for Iris Recognition: An Assessment of the State-of-the-Art
    Czajka, Adam
    Bowyer, Kevin W.
    ACM COMPUTING SURVEYS, 2018, 51 (04)
  • [40] Iris Recognition System
    Kak, Neha
    Gupta, Rishi
    Mahajan, Sanchit
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2010, 1 (01) : 34 - 40