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Iris Recognition by Using Image Processing Techniques

BROWSE_DETAIL_CREATION_DATE: 22-02-2017

BROWSE_DETAIL_IDENTIFIER_SECTION

BROWSE_DETAIL_TYPE: Thesis

BROWSE_DETAIL_SUB_TYPE: Masters

BROWSE_DETAIL_PUBLISH_STATE: Unpublished

BROWSE_DETAIL_FORMAT: PDF Document

BROWSE_DETAIL_LANG: English

BROWSE_DETAIL_SUBJECTS: TECHNOLOGY,

BROWSE_DETAIL_CREATORS: Alhamrouni, Mohamed Ahmed (Author),

BROWSE_DETAIL_CONTRIBUTERS: Şengül, Gökhan (Advisor),

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Iris recognition, histogram of oriented gradient, gray level Co-Occurrence Matrix, local binary pattern


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Iris recognition system has become very important, especially in the field of security,because it provides high reliability. Many researchers have suggested new methods toiris recognition system in order to increase the efficiency of the system. In this thesis,various methods have been proposed to achieve high performance in iris recognition. Inthe proposed system, three feature extraction approaches, Histogram of OrientedGradient (HOG), Gray Level Co-Occurrence Matrix (GLCM) and Local Binary Pattern(LBP) are used to extract the features from iris image. On other hand, two classifiers; KNearestNeighbors (KNN) and Support Vector Machine (SVM) are used in theclassification stage. The iris image passes through several stages before extractingfeatures stage; first, pre-processing stage which includes image resizing that unifies allimages' size, second, segmentation stage which determines the iris region in eye image,finally, normalization stage which converts the iris region to suitable shape with specificdimensions. The proposed methods have been applied on two iris databases, UPOL andIITD. However, the proposed system achieved recognition rate of 100% whenHOG+KNN method is used.


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