scholarly journals Secure Authentication with Iris using Hamming Distance

2019 ◽  
Vol 8 (4) ◽  
pp. 4787-4790
Keyword(s):  
Pattern Matching ◽  
Iris Recognition ◽  
Hamming Distance ◽  
Behavioral Characteristics ◽  
Biometric Authentication ◽  
Previous Knowledge ◽  
Unique Identifier ◽  
Automated Recognition ◽  
Feature Encoding ◽  
Secure Authentication

Biometrics authentication is the automated recognition of physiological or behavioral characteristics of a person without any previous knowledge. It adds a unique identifier and it is extremely difficult to duplicate. One of the most unique biometric authentication structures is iris pattern. It is the most solid and exact distinguishing proof structure existing around. The exhibition of this acknowledgment framework can be estimated with quality and acknowledgment rate. In the proposed work, iris code were generated by the processing the iris image by applying preprocessing, gaber filter, normalization, feature encoding by Fast Fourier Transform and then Hamming distance was used for pattern matching. The overall success rate shows that iris recognition is a reliable and accurate biometric authentication

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.

scholarly journals Future of Cybersecurity: A Study on Biometric Scans

2021 ◽  
Vol 9 (11) ◽  
pp. 1180-1185
Author(s):  
Amogh Joshi
Keyword(s):  
Statistical Analysis ◽  
Human Body ◽  
Iris Recognition ◽  
Facial Recognition ◽  
Voice Recognition ◽  
Biological Characteristics ◽  
Behavioral Characteristics ◽  
Biometric Authentication ◽  
Security Breaches

Abstract: Biometrics is a statistical analysis of people's unique behavioral characteristics. The technology is used for CYBERSECURITY. The basics of biometric authentication is that to stop security breaches by analyzing a person’s unique behavioral characteristics. The term biometrics is derived from the Greek word’s “bios” meaning life and “metricos” meaning to measure. It refers to measurements of physical and biological characteristics of the human body. In this paper, we have studied some biometric methods such as facial recognition, iris recognition, Retinal Recognition, voice recognition. Keywords: Biometrics, Cybersecurity, Biometric Scan, Retinal Scan, Iris Scan, Gait, Voice Recognition.

scholarly journals Improving the IRIS Recognition Under Different Illumination Using RETINEX Algorithms

2018 ◽  
Vol 7 (3.6) ◽  
pp. 81
Author(s):  
Shruthi A. Kumar ◽  
A Baskar
Keyword(s):  
Code Generation ◽  
Iris Recognition ◽  
Noise Suppression ◽  
Hamming Distance ◽  
Gabor Filter ◽  
Distance Metrics ◽  
Illumination Changes ◽  
Retinex Algorithm ◽  
Processing Techniques ◽  
Secure Authentication

Iris detection and recognition provides more accurate and secure authentication nowadays. The probability of any two people having the same iris pattern is nearly zero, even the identical twins will not have the same iris pattern. The noise and illumination changes, challenges iris recognition correctness and security in authentication process. The available recent pre-processing techniques for iris detection address different type of noise suppression and removing unwanted information in iris, but still it strives with illumination issues. In this paper, we proposed Retinex algorithm for improving iris detection rate. The proposed work comprises into three steps: First we proposed Retinex algorithm in pre-processing, it works based on reflectance value of image and skips the illumination value in image, subsequently feature extraction uses Gabor filter for iris code generation. In conclusion, distance metrics Hamming distance used for iris recognition the proposed work evaluated MMU iris database under different illumination conditions and provides better results.  

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

BORDERS AND FINITE AUTOMATA

2007 ◽  
Vol 18 (04) ◽  
pp. 859-871
Author(s):  
MARTIN ŠIMŮNEK ◽  
BOŘIVOJ MELICHAR
Keyword(s):  
Pattern Matching ◽  
Hamming Distance ◽  
Finite Automata ◽  
Music Analysis ◽  
Theoretical Description ◽  
Specific Form ◽  
Distance Measures ◽  
Computer Assisted ◽  
Finite State ◽  
Finite State Transducer

A border of a string is a prefix of the string that is simultaneously its suffix. It is one of the basic stringology keystones used as a part of many algorithms in pattern matching, molecular biology, computer-assisted music analysis and others. The paper offers the automata-theoretical description of Iliopoulos's ALL_BORDERS algorithm. The algorithm finds all borders of a string with don't care symbols. We show that ALL_BORDERS algorithm is an implementation of a finite state transducer of specific form. We describe how such a transducer can be constructed and what should be the input string like. The described transducer finds a set of lengths of all borders. Last but not least, we define approximate borders and show how to find all approximate borders of a string when we concern Hamming distance definition. Our solution of this problem is based on transducers again. This allows us to use analogy with automata-based pattern matching methods. Finally we discuss conditions under which the same principle can be used for other distance measures.

scholarly journals Iris Matching Step Implementation in FPGA

2019 ◽  
Vol 2 (1) ◽  
pp. 26-36
Author(s):  
Aumama M. Farhan ◽  
M. F. Al-Gailani
Keyword(s):  
Execution Time ◽  
Iris Recognition ◽  
Hardware Implementation ◽  
Hamming Distance ◽  
Computation Time ◽  
Recognition System ◽  
Hardware Platform ◽  
System Generator ◽  
Large Memory ◽  
Powerful Strategy

Iris recognition system is broadly being utilized as it has distinctive patterns that gives it a powerful strategy to distinguish between persons for identification purposes. However, this system in this implementation requires large memory capacity and high computation time. These factors make us in a challenge to find a way to run this algorithm in a hardware platform. The hardware implementation features reduce the execution time by exploiting the parallelism and pipeline. The present work addresses this issue when reducing execution time by implementing the matching step using hamming distance algorithm on the target device FPGA KINTEX 7 using Xilinx system generator. The obtained result demonstrates that the execution time has been accelerated to 1.32 ns, which is almost at least four times faster than existing works

Heterogenous Computing on Iris Matching with OpenCL

2016 ◽  
Vol 850 ◽  
pp. 129-135
Author(s):  
Buğra Şimşek ◽  
Nursel Akçam
Keyword(s):  
Graphics Processing Units ◽  
Iris Recognition ◽  
Heterogeneous Computing ◽  
Hamming Distance ◽  
Heterogeneous Systems ◽  
Digital Signal ◽  
Mobile Platforms ◽  
Central Processing ◽  
Field Programmable ◽  
Graphics Processing

This study presents parallelization of Hamming Distance algorithm, which is used for iris comparison on iris recognition systems, for heterogeneous systems that can be included Central Processing Units (CPUs), Graphics Processing Units (GPUs), Digital Signal Processing (DSP) boards, Field Programmable Gate Array (FPGA) and some other mobile platforms with OpenCL. OpenCL allows to run same code on CPUs, GPUs, FPGAs and DSP boards. Heterogeneous computing refers to systems include different kind of devices (CPUs, GPUs, FPGAs and other accelerators). Heterogeneous computing gains performance or reduces power for suitable algorithms on these OpenCL supported devices. In this study, Hamming Distance algorithm has been coded with C++ as a sequential code and has been parallelized a designated method by us with OpenCL. Our OpenCL code has been executed on Nvidia GT430 GPU and Intel Xeon 5650 processor. The OpenCL code implementation demonstrates that speed up to 87 times with parallelization. Also our study differs from other studies, which accelerate iris matching, with regard to ensure heterogeneous computing by using OpenCL.

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%.

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