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Paper Title: Iris Recognition by Using Image Processing Techniques and Feature Extraction
Authors Name: M.Vani Sree , Z.J Rashmitha , S.Prasanth Kumar , S.Davood Akram , B.Srinivasulu
Unique Id: IJSDR1804011
Published In: Volume 3 Issue 4, April-2018
Abstract: Iris recognition system has become very important, especially in the field of security, because it provides high reliability. Many researchers have suggested new methods to iris recognition system in order to increase the efficiency of the system. Various methods have been proposed to achieve high performance in iris recognition. In the proposed system, three feature extraction approaches, Histogram of Oriented Gradient (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; K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) are used in the classification stage. The iris image passes through several stages before extracting features stage; first, pre-processing stage which includes image resizing that unifies all images' size, second, segmentation stage which determines the iris region in eye image, finally, normalization stage which converts the iris region to suitable shape with specific dimensions. The proposed methods have been applied on iris database.However, the proposed system achieved recognition rate of 100% when HOG+KNN method is used.Iris can be the best authenticator in Biometrics as it cannot be destroyed .
Keywords: Iris Recognition; Biometrics;Histogram of Oriented Gradient; Gray Level Co-Occurrence Matrix; Local Binary Pattern,Classifiers.
Cite Article: "Iris Recognition by Using Image Processing Techniques and Feature Extraction ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 4, page no.63 - 69, April-2018, Available :http://www.ijsdr.org/papers/IJSDR1804011.pdf
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Publication Details: Published Paper ID: IJSDR1804011
Registration ID:180118
Published In: Volume 3 Issue 4, April-2018
DOI (Digital Object Identifier):
Page No: 63 - 69
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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