scholarly journals ENHANCED IRIS RECOGNITION BASED ON IMAGE MATCH AND HAMMING DISTANCE

2015 ◽  
Vol 8 (2) ◽  
pp. 1085-1103 ◽  
Author(s):  
Gao Xiaoxing ◽  
Feng Sumin ◽  
Cui Han
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Image Match

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

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%.

scholarly journals A Review of Iris Recognition Algorithms

2017 ◽  
Vol 1 (4-2) ◽  
pp. 175
Author(s):  
Abdulrahman Aminu Ghali ◽  
Sapiee Jamel ◽  
Kamaruddin Malik Mohamad ◽  
Nasir Abubakar Yakub ◽  
Mustafa Mat Deris
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Gabor Filter ◽  
Recognition System ◽  
Personal Identification ◽  
Border Control ◽  
Biometric System ◽  
Rubber Sheet ◽  
Automated Teller Machines ◽  
Recognition Algorithms

With the prominent needs for security and reliable mode of identification in biometric system. Iris recognition has become reliable method for personal identification nowadays. The system has been used for years in many commercial and government applications that allow access control in places such as office, laboratory, armoury, automated teller machines (ATMs), and border control in airport. The aim of the paper is to review iris recognition algorithms. Iris recognition system consists of four main stages which are segmentation, normalization, feature extraction and matching. Based on the findings, the Hough transform, rubber sheet model, wavelet, Gabor filter, and hamming distance are the most common used algorithms in iris recognition stages.  This shows that, the algorithms have the potential and capability to enhanced iris recognition system. 

scholarly journals An Accurate and Efficient User Authentication Mechanism on Smart Glasses Based on Iris Recognition

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yung-Hui Li ◽  
Po-Jen Huang
Keyword(s):  
Mobile Devices ◽  
Iris Recognition ◽  
Hamming Distance ◽  
User Authentication ◽  
Infrared Camera ◽  
Modern Society ◽  
Infrared Light ◽  
Recognition Mechanism ◽  
Authentication Mechanism ◽  
Smart Glasses

In modern society, mobile devices (such as smart phones and wearable devices) have become indispensable to almost everyone, and people store personal data in devices. Therefore, how to implement user authentication mechanism for private data protection on mobile devices is a very important issue. In this paper, an intelligent iris recognition mechanism is designed to solve the problem of user authentication in wearable smart glasses. Our contributions include hardware and software. On the hardware side, we design a set of internal infrared camera modules, including well-designed infrared light source and lens module, which is able to take clear iris images within 2~5 cm. On the software side, we propose an innovative iris segmentation algorithm which is both efficient and accurate to be used on smart glasses device. Another improvement to the traditional iris recognition is that we propose an intelligent Hamming distance (HD) threshold adaptation method which dynamically fine-tunes the HD threshold used for verification according to empirical data collected. Our final system can perform iris recognition with 66 frames per second on a smart glasses platform with 100% accuracy. As far as we know, this system is the world’s first application of iris recognition on smart glasses.

IRIS RECOGNITION USING ADABOOST AND LEVENSHTEIN DISTANCES

2012 ◽  
Vol 26 (02) ◽  
pp. 1266001 ◽  
Author(s):  
JOAN CLIMENT ◽  
ROBERTO A. HEXSEL
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Decision Function ◽  
Gabor Wavelets ◽  
Levenshtein Distance ◽  
Processor Array ◽  
Processing Elements ◽  
Time Operation ◽  
Real Time Operation ◽  
Selection Of

This paper presents an efficient IrisCode classifier, built from phase features which uses AdaBoost for the selection of Gabor wavelets bandwidths. The final iris classifier consists of a weighted contribution of weak classifiers. As weak classifiers we use three-split decision trees that identify a candidate based on the Levenshtein distance between phase vectors of the respective iris images. Our experiments show that the Levenshtein distance has better discrimination in comparing IrisCodes than the Hamming distance. Our process also differs from existing methods because the wavelengths of the Gabor filters used, and their final weights in the decision function, are chosen from the robust final classifier, instead of being fixed and/or limited by the programmer, thus yielding higher iris recognition rates. A pyramidal strategy for cascading filters with increasing complexity makes the system suitable for real-time operation. We have designed a processor array to accelerate the computation of the Levenshtein distance. The processing elements are simple basic cells, interconnected by relatively short paths, which makes it suitable for a VLSI implementation.

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