iris identification IEEE PAPER 2016






User Identification Using Iris Scan
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Abstract:This paper delivers a iris coding method for effective recognition of an individual. An algorithm that is based on person iris independent of spatial position, orientation and center frequencies of the iris image. The fact that the iris is protected behind the eyelid,

Sum Rule Based Matching Score Level Fusion of Fingerprint and Iris Images for Multimodal Biometrics Identification
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Abstract–Basic aim of a biometric system is automatically discriminate between subjects as well as protects data. It also protects resources access from unauthorized users. In biometric system physical or behavioral traits are used for recognition purpose. A multimodal

Iris Recognition Based on Extreme Point Identification using Feature Extraction
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Abstract: The use of human identification has become increasingly in demand in today's society. The human iris is one of the most unique biometrics available to use in the identification of an individual. A biometric is characteristic of human body that can be used

Human Identification Using FKP, IRIS and FV Images
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Abstract Biometric Recognition will provide strong link between individual and claimed identity. In modern years, biometrics is largely used for personal recognition. In this paper, a new combined biometric system, namely, Finger-Knuckle-Print (FKP), Finger vein and

BIOMETRIC IDENTIFICATION USING IRIS RECOGNITION SYSTEM
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Abstract:Biometric Recognition being the most appropriate and up-to-date identification technique is used in different fields due to uniqueness of the various physiological and behavioral traits like finger prints, hand geometry, face recognition, iris recognition, voice

A System for Non-Intrusive Human Iris Acquisition and Identification.
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image is focussed. Another sys- tem for iris identification requiring similar levels of user cooperation is described in . In this paper, we describe an active system for image acquisition using machine vision techniques. The user

Eyelid Localization for Iris Identification .
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This article presents a new eyelid localization algorithm based on a parabolic curve fitting. To deal with eyelashes, low contrast or false detection due to iris texture, we propose a two steps algorithm. First, possible edge candidates are selected by applying edge detection on

Iris recognition: an emerging biometric technology
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In network security there is a vital emphasis on the automatic personal identification. Due to its inherent advantages biometric based verification especially iris identification is gaining a lot of attention The iris identification is basically divided in four steps

Iris identification based on optimized lab histograms applied to iris partitions
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A method for iris identification based on local color distribution is proposed. Color feature vectors are extracted from high quality iris images, manually segmented from the database of 384 eye images produced by the Palacký University, Olomouc (UPOL), Czech Republic

Person identification technique using human iris recognition
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In 198 they began collaborating with computer scientist John Daugman of Cambridge Uni- versity in England to develop iris identification software who published his first promising results in 1992 . Later on a little similar works have been investigated, such as R.Wildes [5

Recognition of human iris patterns for biometric identification
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Page 1. Recognition of Human Iris Patterns for Biometric Identification Libor Masek This report is submitted as partial fulfilment of the requirements for the Bachelor of Engineering degree of the School of Computer Science and

A new iris identification method based on ridgelet transform
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Iris recognition system provides an approach for individual identification and is regarded as the sophisticated biometric identification system. Therefore, the exclusive features of iris patterns should be extracted and processed. In this paper, a new feature extraction method

Impact of Resolution and Blur on Iris Identification
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Iris recognition is increasingly employed as a biometric modality to improve the security across the government, public, and private sectors; however, the limitations of iris recognition are yet to be fully understood. Several approaches have been previously

Iris identification system based on RLM texture features
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Among biometric identification technologies, iris recognition has attracted lots of attention because of uniqueness and long term stability. In this paper, a new iris recognition system based on texture has been proposed and used for identification of person. Texture features

Biometric Iris Identification in Bovines
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Animal identification has become a topic of increasing worldwide importance as this method is desirable for genetic and performance monitoring and other applications such as animal health and food safety. In particular, bovine identification aims to avoid the problems caused

Development a new algorithm for iris biometric recognition
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Also the time required for iris identification is less than one second. Index Terms Recognition, biometric, iris, hough transforms, gabor wavelets The algorithm gives the accuracy of more than 99.99%. Also the time required for iris identification is less than one second

Iris Identification Using Two Activation Function Wavelet Networks
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ABSTRACT A variety of researches Dealt with the iris identification in different ways and Showed different results. A new system for personal identification based on iris patterns is presented in this paper. We propose to use two activation function wavelet neural network

Iris Identification System Using Tree-Structured Wavelet Algorithm.
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The unique iris structures motivate the development of an automatic identification system based on iris characteristic. Texture analysis with multichannel filtering approach is meant to extract feature from iris texture images and encode them into a compact and unique

Implementation on SoPC of Algorithms Dedicated to Iris Identification
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This paper presents a biometric technology for identifying people based on iris. An algorithm using wavelet packet analysis is presented. The identification process starts with iris capture, localization and unwrapping. Then wavelet transform is applied and a signature is extracted

Person identification through IRIS recognition
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No. January Actual iris identification can be broken down into four fundamental steps. First, a person stands in front of the iris identification system, generally between one and three feet away, while a wide angle camera calculates the position of their eye

Personal Identification with Human Iris Recognition based on Wavelet Transform.
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Boles and Boashash proposed an iris identification system in which zero-crossing of the wavelet transform at various resolution levels is calculated over concentric circles on the iris, and the resulting 1-D signals are compared with the model features using different

Iris recognition using texture features extracted from haarlet pyramid
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In all 384 queries were tested on our database for analysing the performance of proposed iris identification techniques. The table (TABLE 1) gives the percentage of FAR and GAR for iris identification using variations in Haarlet based techniques

Extract and classification of iris images by fractal dimension and efficient color of iris
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Password and Comparison 5 2 8 1 2. IRIS BASED IDENTIFICATION SYSTEMS In 199 John Daugman presented the first iris identification system by Gabor wavelet transform. Daugman idea was based on transforming iris image to a 256 Byte code that is named Iris Code

DWT and DCT based robust iris feature extraction and recognition algorithm for biometric personal identification
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vectors is more. 3. PROPOSED SCHEME The proposed scheme consists of following processing stages as shown in Figure 1 and the detailed procedure in case of iris identification process is as follows, 3.1 IRIS Recognition

Iris recognition for personal identification using LAMSTAR neural network
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Table1. Comparison between performance of our proposed method and Duagman 6. CONCLUSION AND FUTURE WORK In this work a new neural network method is presented for iris identification . A template is achieved using Image processing techniques

Iris data parametrization by Hermite projection method
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Abstract Hermite projection method is used for human iris identification . Expansion of iris intensity information into a series of eigenfunctions of Fourier transform enables us to perform information analysis of the signal and its Fourier transform at the same time

Iris Feature Detection using Split Block and PSO for Iris Identification System
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The past decade has seen the rapid development of iris identification in many approaches to identify unique iris features such as crypts. However, it is noted that, unique iris features change due to iris aging, diet or human health conditions. The changing of iris features

An enhanced segmentation approach for iris detection
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Furthermore, an enhanced method based on the techniques of the mentioned two methods is proposed, which can guarantee the accuracy of the iris identification system. The proposed method takes into account the elliptical shape of the pupil and iris

Identification of People by Iris Recognition
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Two different approaches for iris identification presented by Rajat Garg, Vikrant Gupta, Vineet Agrawal template matching and average value method, in template matching method it compares the user template with templates from the database using a matching metric

IRIS texture analysis and feature extraction for biometric pattern recognition
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Actual iris identification can be broken down into four fundamental steps. First, a person stands in front of the iris identification system, generally between one and three feet away, while a wide angle camera calculates the position of their eye

Achieving Privacy-Preserving Iris Identification Via El Gamal
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Currently, many biometric systems maintain the users biometrics and templates in plaintext format, which brings great privacy risk to uses biometric information. Biometrics are unique and almost unchangeable, which means it is a great concern for users on whether their

Texture detection for segmentation of iris images
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personal identification. However, this was only documented by James Doggarts in 1949. The idea of iris identification for automated recognition was finally patented by Aran Safir and Leonard Flom in 1987. Although they had

Iris recognition using non filter-based technique
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Fig. 2 3. Results: Our new technique is found to have good performance characteristics in the sense it establishes that non filter based techniques can be successfully used for iris identification . It gives an EER of 9.32 % and a d- prime value of 1.632

Iris recognition using circular Hough transform
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2 No. Korea, pp 1220-122 2001. S. Noh, K. Pae, C. Lee and J. Kim Multiresolution independent component analysis for iris identification , The 2002 International Technical Conference on Circuits/Systems, Computers and Communications, Phuket, Thailand

Fingerprints, Iris and DNA features based multimodal systems: a review
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Page 1. IJ Information Technology and Computer Science, 201 0 88-111 Published Online January 2013 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijitcs.2013.02.10 Copyright 2013 MECS IJ Information Technology and Computer Science, 201 0 88-111

Biometrics in IRIS technology: A survey
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Figure 7: Retina Scan Iris security system is smoother, smarter and more secure identification system Automated high speed iris capturing and precision identification make iris identification system the worlds most advanced access and entry point security identification system

Efficient iris recognition through improvement in iris segmentation algorithm
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In 199 Daugman developed the iris identification software . The proposed method differs in the process of iris code generation for pattern matching. The Daugman system has been tested for a billion images and the failure rate was found to be very low

A closure looks to Iris Recognition system
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VI. CONCLUSION Iris identification was considered one of the most robust ways to identify humans Iris identification provides convenience to the human users and is widely accepted. Dr. John Daugman developed the theoretical research and algorithms

IREX IX Part One: Performance of Iris Recognition Algorithms
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Performance was measured for 46 matching algorithms over a set of approximately 700K field-collected iris images. This report is very similar to IREX IV: Part Evaluation of Iris Identification Algorithms in both format and scope. Key Results

Efficient small template iris recognition system using wavelet transform
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Experimental results are given in section and Section 6 concludes this paper. 2. RELATED WORK Iris identification using analysis of the iris texture has attracted a lot of attention and researchers have presented a variety of approaches in the literature

Performance of Personal Identification System Technique Using Iris Biometrics Technology.
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Email ID: srinivasan_gasc@yahoo.com Abstract The Iris identification as one of the significant techniques of biometric identification systems s and iris recognition algorithm is described The iris identification is basically divided in four steps. A. Capturing the Image

Personal identification based on iris texture analysis using semivariogram and correlogram functions
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These functions (semivariogram and correlogram) are used in other areas of knowledge (for example in, geology and ecology) but not yet explored in iris identification . Our work is the first which explores these functions in this area

Learning hierarchical visual codebook for iris liveness detection
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The forth set is iris identification based on fake iris images. 4.1 4.4. Identify fake irises To verify whether the fake iris image can be used to at- tack the system or not, we do experiments about fake iris identification by comparing fake irises with the genuine ones

Iris features via fractal functions for authentication protocols
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method. Keywords: Fractal, Iterated function system, Iris identification Authentication 1. Introduction 14]. Iris identification is based on features that can be analyzed to recognize authorized people . In 201 Jampour et al

Biometric Solution for Person Identification Using Iris Recognition System
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for a biometric. In 198 they began collaborating with computer scientist John Daugman of Cambridge University in England to develop iris identification software who published his first promising results in 1992. Later on a
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