scholarly journals An optimized rubber sheet model for normalization phase of IRIS recognition

2020 ◽  
Vol 1 (3) ◽  
pp. 126-134
Author(s):  
Selvamuthukumaran S. ◽  
Ramkumar T. ◽  
Shantharajah Shantharajah
Keyword(s):  
Iris Recognition ◽  
Histogram Equalization ◽  
Normalization Method ◽  
Polar Coordinates ◽  
Experimental Result ◽  
Biometric Authentication ◽  
Spherical Coordinates ◽  
Rubber Sheet ◽  
Segmented Image ◽  
Human Iris

Iris recognition is a promising biometric authentication approach and it is a very active topic in both research and realistic applications because the pattern of the human iris differs from person to person, even between twins. In this paper, an optimized iris normalization method for the conversion of segmented image into normalized form has been proposed. The existing methods are converting the Cartesian coordinates of the segmented image into polar coordinates. To get more accuracy, the proposed method is using an optimized rubber sheet model which converts the polar coordinates into spherical coordinates followed by localized histogram equalization. The experimental result shows the proposed method scores an encouraging performance with respect to accuracy.

scholarly journals Multibiometric authentication with MATLAB simulation

2018 ◽  
Vol 7 (1.7) ◽  
pp. 47
Author(s):  
P Selvarani ◽  
N Malarvizhi
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Research Work ◽  
Histogram Equalization ◽  
Fingerprint Recognition ◽  
Morphological Operations ◽  
Matlab Simulation ◽  
Rubber Sheet ◽  
Recognition Process ◽  
Canny Edge

Multimodal Biometric Authentication has been used as more security purpose for establishing the user Identification, Authentication and Verification purpose. Multimodal Biometric like Fingerprint and iris are used in this research work for authentication purpose using Matlab simulation. Fingerprint recognition process like Image Enhancement, binarization, Segmentation, thinning, Minutia marking, and Matching are performed with various techniques like Histogram Equalization, Adaptive Binarization, Morphological operations, Minutiae based techniques etc.,Iris recognition process like Segmentation, Normalization, Encoding and Matching are performed with various techniques like Canny edge detection, Daughman’s Rubber sheet model, Hamming Distance etc., can be applied for Fingerprint and iris recognition for authentication purpose. Finally Performance the measure of Precision, Recall, F-Score and Accuracy has evaluated in both fingerprint and iris. It can be concluded Iris Accuracy is higher 0.96% compared with fingerprint accuracy 0.81%.

SISTEM PENGENALAN MANUSIA MELALUI KEUNIKAN FISIOLOGIS SELAPUT PELANGI MATA DENGAN MENGGUNAKAN FILTER LOG GABOR

KONVERGENSI ◽  
2019 ◽  
Vol 13 (1) ◽  
Author(s):  
Bima Agung Pratama ◽  
Fajar Astuti Hermawati
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Rubber Sheet ◽  
Log Gabor

Penelitian ini mengajukan sebuah sistem pengenalan manusia melalui karakteristik pola fisiologis selaput pelangi (iris) matanya. Pengenalan selaput pelangi mata (iris recognition) merupakan suatu teknologi pengolahan citra yang digunakan untuk mendeteksi dan menampilkan selaput pelangi (iris) pada alat indera mata manusia saat kelopak mata terbuka. Terdapat beberapa tahap dalam proses pengenalan menggunakan pola iris mata manusia. Langkah pertama adalah melakukan proses segmentasi untuk mendapatkan daerah selaput pelangi (iris) mata yang berbentuk melingkat dengan menggunakan metode operator integro-diferensial. Selanjutnya dilakukan proses normalisasi hasil segmentasi menjadi bentuk polar dengan menerapkan metode metode Daughman’s rubber sheet model. Setelah itu diterapkan proses ekstraksi fitur atau pola dari citra ternormalisasi menggunakan filter Log-Gabor. Pencocokan untuk mengukur kesamaan antara pola iris mata manusia dengan pola-pola dalam basisdata sistem dilakukan menggunakan Hamming distance. Dalam percobaan pengenalan individu menggunakan basisdata iris mata MMU diperoleh akurasi sebesar 98%. Kata Kunci: Pengenalan selaput pelangi, Pengenalan iris mata, Filter log-Gabor, Segmentasi citra, Sistem biometrik

USABLE SECURITY IN BIOMETRIC AUTHENTICATION SYSTEMS

2021 ◽  
Vol 17 (1) ◽  
pp. 287-292
Author(s):  
Adriana-Meda UDROIU ◽  
Ștefan-Antonio DAN-ȘUTEU
Keyword(s):  
Iris Recognition ◽  
Accurate Method ◽  
Biometric Authentication ◽  
Usable Security ◽  
Security Systems ◽  
Field Methods ◽  
Secure Systems ◽  
Authentication System ◽  
Secure Authentication ◽  
Pattern Variability

Abstract: We introduce the term usable security to refer to security systems, models, mechanisms and applications that have as the main goal usability. Secure systems cannot exist without secure authentication methods. Thus we outline biometric authentication methods and we focus on iris recognition because is the most reliable and accurate method for human identification]. The most important advantage of iris biometric over other biometrics is that irises have enormous pattern variability meaning that the variation between individual is almost maximum and variation for any person across time or conditions is minimum. Taking into consideration this observations, this survey covers researches in this field, methods of technical implementation and the usability of this method as an authentication system on iOS environment.

Morphological Contour Based Blood Vessel Segmentation in Retinal Images Using Otsu Thresholding

2018 ◽  
Vol 9 (4) ◽  
pp. 48-63 ◽  
Author(s):  
S. Saranya Rubini ◽  
A. Kunthavai ◽  
M.B. Sachin ◽  
S. Deepak Venkatesh
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Early Stage ◽  
Histogram Equalization ◽  
Vessel Segmentation ◽  
Contour Detection ◽  
Experimental Result ◽  
Blood Vessel Segmentation ◽  
Otsu Thresholding ◽  
Sensitivity Specificity

Retinal image analysis plays an important part in identifying various eye related diseases such as diabetic retinopathy (DR), glaucoma and many others. Accurate segmentation of blood vessels plays an important part in identifying the retinal diseases at an early stage. In this article, an unsupervised approach based on contour detection has been proposed for effective segmentation of retinal blood vessels. The proposed morphological contour-based blood vessel segmentation (MCBVS) method performs preprocessing using contrast limited adaptive histogram equalization followed by alternate sequential filtering to generate a noise-free image. The resultant image undergoes Otsu thresholding for candidate extraction followed by contour detection to properly segment the blood vessels. The MCBVS method has been tested on the DRIVE dataset and the experimental result shows that the proposed method achieved a sensitivity, specificity and accuracy of 58.79%, 90.77% and 86.7%, respectively. The MCBVS method performs better than the existing methods Sobel, Prewitt and Modified U-Net in terms of accuracy.

Iris Localisation Using Fuzzy Centre Detection (FCD) Scheme and Active Contour Snake

2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Masrullizam Mat Ibrahim ◽  
John S. Soraghan ◽  
Nurulfajar Abd Manap
Keyword(s):  
Active Contour ◽  
Iris Recognition ◽  
Image Database ◽  
Target Object ◽  
Recognition Algorithm ◽  
Experimental Result ◽  
Georgia Tech ◽  
Fuzzy Membership Functions ◽  
Main Target ◽  
Snake Algorithm

Iris localisation is a crucial operation in iris recognition algorithm and also in applications, where irises are the main target object. This paper presents a new method to localise iris by using Fuzzy Centre Detection (FCD) scheme and active contour Snake. FCD scheme which consists of four fuzzy membership functions is purposely designed to find a centre of the iris. By using the centre of iris as the reference point, an active contour Snake algorithm is employed to localise the inner and outer of iris boundary. This proposed method is tested and validated with two categories of image database; iris databases and face database.  For iris database, UBIRIS.v1, UBIRIS.v2, CASIA.v1, CASIA.v2, MMU1 and MMU2 are used. Whilst for face databases, MUCT, AT&T, Georgia Tech and ZJUblink databases are chosen to evaluate the capability of proposed method to deal with the small size of the iris in the image database. Based on the experimental result, the proposed method shows promising results for both types of databases, including comparison with the some existing iris localisation algorithm.  

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