Iris Recognition and Ocular Biometrics - The Salient Features

2008 ◽  
Author(s):  
Barbara Pierscionek ◽  
Stephen Crawford ◽  
Bryan Scotney
Keyword(s):  
Iris Recognition ◽  
Salient Features

IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

2018 ◽  
Vol 1 (2) ◽  
pp. 34-44
Author(s):  
Faris E Mohammed ◽  
Dr. Eman M ALdaidamony ◽  
Prof. A. M Raid
Keyword(s):  
Iris Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Individual Identification ◽  
Work Place ◽  
Identification Process ◽  
Finger Vein ◽  
Noise Point ◽  
Vein Recognition ◽  
A New Technique

Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new technique named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of tremendous key-point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and improvement steps are critical for SIFT-based recognition for iris and finger vein , and the proposed technique can accomplish satisfactory recognition performance. Keywords: SIFT, Iris Recognition, Finger Vein identification and Biometric Systems.   © 2018 JASET, International Scholars and Researchers Association    

Survey on Segmentation to Iris Recognition System

2012 ◽  
Vol 3 (4) ◽  
pp. 514-515
Author(s):  
Meenakshi BK Meenakshi BK ◽  
◽  
Prasad M R Prasad M R
Keyword(s):  
Iris Recognition ◽  
Recognition System

Metastable Defects in the Amorphous Silicon-Germanium Alloys

2003 ◽  
Vol 762 ◽  
Author(s):  
J. David Cohen
Keyword(s):  
Amorphous Silicon ◽  
Silicon Germanium ◽  
Dangling Bonds ◽  
Annealing Behavior ◽  
Fundamental Properties ◽  
Silicon Materials ◽  
Salient Features ◽  
The Individual ◽  
Amorphous Silicon Germanium ◽  
Silicon Germanium Alloys

AbstractThis paper first briefly reviews a few of the early studies that established some of the salient features of light-induced degradation in a-Si,Ge:H. In particular, I discuss the fact that both Si and Ge metastable dangling bonds are involved. I then review some of the recent studies carried out by members of my laboratory concerning the details of degradation in the low Ge fraction alloys utilizing the modulated photocurrent method to monitor the individual changes in the Si and Ge deep defects. By relating the metastable creation and annealing behavior of these two types of defects, new insights into the fundamental properties of metastable defects have been obtained for amorphous silicon materials in general. I will conclude with a brief discussion of the microscopic mechanisms that may be responsible.

A Survey on Iris Recognition System

2019 ◽  
Vol 7 (7) ◽  
pp. 302-307
Author(s):  
Prabhat Kumar ◽  
Manish Ahirwar ◽  
Anjna Deen
Keyword(s):  
Iris Recognition ◽  
Recognition System

Mobile Voting System using Iris Recognition and Cryptography Techniques

2011 ◽  
Vol 4 (3) ◽  
pp. 38-42
Author(s):  
K. Gopal ◽  
◽  
S. Praveen ◽  
N. Suthanthira Vanitha ◽  
◽  
...  
Keyword(s):  
Iris Recognition ◽  
Voting System

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

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