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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    An Iris detection and recognition system to measure the performance of e-security

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    12201100.pdf (814.4Kb)
    Date
    4/21/2016
    Publisher
    BRAC University
    Author
    Anwar, A.M. Shahed
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/10361/5400
    Abstract
    Biometric is a system to identify the individual human by extracting distinguishable features from that particular person. Among many other biometric systems the iris recognition system is most accurate one right now since it has a high recognition rate. This thesis is proposing a system with four major division in the process: Segmentation, Normalization, Feature encoding and Matching. At early stage, Histogram equalization is used on the input image and to detect the objects present in the image, Canny Edge Detection model is employed. Inner circular boundary and center of the pupil in the Iris region is detected by using Hough Transformation. A circle is drawn with the help of Mid-Point Circle drawing algorithm which center is as same as pupil center and hence, outer circular boundary of the iris region can be detected. For the normalization, Daugman’s Rubber Sheet model is used and in the feature encoding process, instead of Gabor filter to extract feature from the iris image, Log-Gabor filter is used in this thesis since it has non-zero DC component advantage over Gabor filter. Last but not the least, Hamming Distance is used to compare two binary iris template for matching purpose.
    Keywords
    Computer science and engineering; E-security
     
    Description
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 36-37).
     
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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