Performances of proposed normalization algorithm for iris recognition

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title Performances of proposed normalization algorithm for iris recognition
 
Creator Jusman, Yessi
Ng, Siew Cheok
Hasikin, Khairunnisa
 
Subject Iris recognition; Feature extraction; ROI; GLCM; Dicriminant Analysis
 
Description Iris recognition has very high recognition accuracy in comparison with many other biometric features. The iris pattern is not the same even right and left eye of the same person. It is different and unique. This paper proposes an algorithm to recognize people based on iris images. The algorithm consists of three stages. In the first stage, the segmentation process is using circular Hough transforms to find the region of interest (ROI) of given eye images. After that, a proposed normalization algorithm is to generate the polar images than to enhance the polar images using a modified Daugman’s Rubber sheet model. The last step of the proposed algorithm is to divide the enhance the polar image to be 16 divisions of the iris region. The normalized image is 16 small constant dimensions. The Gray-Level Co-occurrence Matrices (GLCM) technique calculates and extracts the normalized image’s texture feature. Here, the features extracted are contrast, correlation, energy, and homogeneity of the iris. In the last stage, a classification technique, discriminant analysis (DA), is employed for analysis of the proposed normalization algorithm. We have compared the proposed normalization algorithm to the other nine normalization algorithms. The DA technique produces an excellent classification performance with 100% accuracy. We also compare our results with previous results and find out that the proposed iris recognition algorithm is an effective system to detect and recognize person digitally, thus it can be used for security in the building, airports, and other automation in many applications.
 
Publisher Universitas Ahmad Dahlan
 
Contributor Universitas Muhammadiyah Yogyakarta
 
Date 2020-07-12
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/397
10.26555/ijain.v6i2.397
 
Source International Journal of Advances in Intelligent Informatics; Vol 6, No 2 (2020): July 2020; 161-172
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/397/ijain_v6i2_p161-172
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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