Biometrics - Iris Recognition

Gait recognition is a technique that identifies or verifies people based upon their walking patterns. Smartwatches, which contain an accelerometer and gyroscope have recently been used to implement gait-based biometrics. However, this prior work relied upon data from single sessions for both training and testing, which is not realistic and can lead to overly optimistic performance results. This paper aims to remedy some of these problems by training and evaluating a smartwatch-based biometric system on data obtained from different days. Also, it proposes an advanced feature selection approach to identify optimal features for each user. Two experiments are presented under three different scenarios: Same-Day, Mixed-Day, and Cross-Day. Competitive results were achieved (best EERs of 0.13% and 3.12% by using the Same day data for accelerometer and gyroscope respectively and 0.69% and 7.97% for the same sensors under the Cross-Day evaluation. The results show that the technology is sufficiently capable and the signals captured sufficiently discriminative to be useful in performing gait recognition.

The word biometrics refers to the use of physiological or biological characteristics of human to recognize and verify the identity of an individual. Face is one of the human biometrics for passive identification with uniqueness and stability. In this manuscript we present a new face based biometric system based on neural networks supervised self organizing maps (SOM). We name our method named SOM-F. We show that the proposed SOM-F method improves the performance and robustness of recognition. We apply the proposed method to a variety of datasets and show the results.

In this paper we propose an adaptive fusion approach for iris biometric. The proposed fusion method incorporates four matching algorithms using feature quality and relative entropy to enhance iris fusion performance. This method introduces relative entropy measure to the fusion process to assign low weighting coefficients to features with less information and higher weights to features with more information. We investigated the parameters which influences the rejection rates and acceptance rates to determine the optimal equal error rate. The best equal error rates were aimed at high recognition accuracy. The proposed method was tested on two public iris databases. CASIA left eye images produced 99.36 % recognition accuracy and 0.041% equal error rate as compared to 98.93 % recognition accuracy and 0.066 % error rate produced by the weighted sum fusion. For the CASIA right eye images, the proposed method produced 99.18 % recognition accuracy and 0.087 % equal error rate as compared to weighted sum fusion with 98.81 % recognition accuracy and 0.096 % equal error rate. From the UBIRIS database, the proposed method produced 99.59 % recognition accuracy and 0.038 % equal error rate as compared to 98.53 % recognition accuracy and 0.074 % equal error rate produced by weighted sum fusion. The proposed method show improved recognition performance in terms of AUC and the EER.

One of the most difficult problems in era of Demonization was adopting Biometric payment, which may vary depending on environmental or personal causes. Addressing this problem, this paper presents a insite in the mobile banking transactions space which will surely alleviate the rural and common man difficulty of cashless transactions in the phase of Demonetization in India.

Effective management of projects is increasingly becoming important for organisations to remain competitive in today's dynamic business environment. The use of benchmarking is widening as a technique for supporting project management. Benchmarking is the search of best practices that will lead to superior performance in some business activity. Benchmarking has been recognised as one of the most responsive evaluation tool for performance improvement within organisations by creating a culture of continuous improvement from learning best management practices. This paper presents how benchmarking principles can be applied to improve project management process and performance. The benefits and challenges of benchmarking management of projects are also discussed.

Biometrics represents a return to a traditional way of identifying someone relying on what that person is instead of what that person knows or owns. Even though the significant amount of research that has been done in this field, there is still much to do as new emerging scenarios of application appear everyday. Biometric recognition systems are no longer restricted to forensic investigation or control management of employees. They have been gaining a visibility and applicability in daily use devices which reinforces their usability in all aspects of our day to day life. With this spread of biometric applications, nowadays commonly found in our laptops, our smart phones, some bank management services and airport custom services, a necessity for improved security also is rising. The importance of protecting our identity and our data has become crucial as our devices are filled with sensible information of many kinds. Therefore the presentation attack or liveness detection methods as ...

The problem of voting is still critical in terms of safety and security. This paper deals with the design and development of a web-based voting system using cloud computing and aadhaar card in order to provide a high performance with high security to the voting system. We also use web technology to make the voting system practical. The proposed Online Voting System allows the voters to authenticate using aadhaar no which is then matched with an already saved within a database that is retrieved from aadhaar card database of the government. The voting system is managed in a simpler way as all the users must login by aadhaar card number and password and click on his/her favorable candidates to cast the vote. This will increase the voting percentage in India and reduces the cost of voting process. By using aadhaar card identification it provides enough security which reduces the false votes.

Biometric-based recognition systems have overcome passive issues of traditional human authentication systems. However, security theft and privacy invasion are two passive issues that still persist in the effective deployment of biometric-based authentication systems. Compromise of biometric data can potentially lead to serious security violation as the user's biometric trait cannot be changed. In order to prevent the invasion of biometric templates, it is desired to morph the original biometric template through non-invertible or irreversible transformation function. This transformed template is referred to as cancelable template and can be replaced or reissued in case of compromise. In this paper, we propose a novel cancelable iris template generation technique based on randomized look-up table mapping. The technique utilizes a decimal vector generated from a rotation-invariant feature vector. The feature vector is generated using 1-D Log Gabor filter applied to the iris image. Experiments carried out on various iris databases confirm the efficacy of the proposed approach. After applying the template protection mechanism, we have achieved Equal Error Rate (EER) of 0.37%, 0.43% and 0.79% for CASIA-V 1.0, CASIA-V3-Interval and ICE 2005 iris databases, respectively. Moreover, the transformation preserves the irreversibility, revocability and diversity properties of the concealable iris templates.

This paper presents comparison concerning various biometric systems simply by defining their advantages and disadvantages. A brief introduction is usually offered regarding commonly used biometrics, including, Face, Iris, Fingerprint, Finger Vein, Lips, Voice. The comparison criteria list introduced is restricted to accuracy, size of template, cost, security level, and long term stability.

In today’s advanced era it is needed to design the
system which will give highly accurate results regarding
biometric human identification. Iris recognition is considered to
be the best biometric human identification system. Daugman’s
method for iris recognition is considered as the efficient &
accurate iris recognition system as per previous research. This
technique is discussed in detail in this paper.

The purpose of this paper is to gain a better understanding of
user acceptance of Biometric Technologies (BT) at outdoor
music festivals in the United Kingdom. While research on such
technologies, such as facial recognition is limited in the events
context, they have already been deployed at music festivals to
deal with issues of security, safety and crowd management.
Using an extended Technology Acceptance Model (TAM), a
self-administered questionnaire was completed by young
adults in the United Kingdom who had previously been to a
music festival. The study found factors such as privacy, reliability and accuracy did not have a significant impact on user
acceptance. Other factors, such as trust, compatibility and convenience were found to have a significant positive impact on
perceived ease of use, perceived usefulness and attitude to
use. As the findings indicate that accuracy and privacy do not
impact BT acceptance, the paper explores how organizers can
be transparent and accountable as to their intentions to use
BT, so as to justify the usefulness of BT to attendees, artists,
regulators and authorities.

Authentication plays a very critical role in security related applications. This is obvious from the breaches of information systems recorded around the world. This has become a major challenge to ecommerce and many other applications. One of the techniques that is implemented today to improve information security is biometrics, and this is gaining attention as the days go by. Having realized its value, biometrics is used in most systems today for the verification and identification of users as it overcomes the problems of being stolen, borrowed, forged or forgetting. In this paper therefore, we show the origin and types of biometrics, their areas of application, and what to look out for in selecting a biometric technology.

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IEEE˜ IEEE˜Abstract-Image quality assessment plays an important role in enhancing the performance of pattern recognition systems, including biometric systems. Although, quality assessment methods have been utilized for iris recognition on adults they have not been investigated on iris recognition for children. Iris recognition on children is difficult because of their uncooperative nature and may result in lower quality iris samples. In this study, we applied four existing quality assessment methods, light variation, pupil dilation, off-angle, and pixel count to data we collected from children and the CASIA database with iris images from adults. The results indicate that once the image without any visible iris area are removed, using an automated process, then the remaining images for children produces similar quality assessment distributions as those of iris images from adults. This study is the first step in creating an iris recognition system for children.

Solved – Fingerprint Enrollment, Verification and Identification Module using DigitalPersona U.are.U 4500 & 4000B in C#., if you have being looking for source code on how do I capture fingerprint in C# by using DigitalPersona 4500 & 4000B SDK or how to use biometric fingerprint scanner in c#, then you are at the right place, because your problem has being solved.

Our Module is very simple and easy to use in accordance with the demands of your application needs. The Module provides more advanced solution, suitable for those who need more freedom in creative. The functions in the module are not too basic, the functions concept are instant, you simply call the functions required for registering and verify fingerprints then the module will do the registration process and verification process without you directly involved in it. The registration process will produce a fingerprint template in a binary format that is easy to be stored in SQL Database and distributed. When you want to identify a finger, the templates are used to compare the fingerprints scanned. You will get the results of the verification whether the same finger or not. Our module will greatly save your time to integrate fingerprint technology into any application required. You can use our module on biometric fingerprint attendance system in c#.

ID2020 and partners launch program to provide digital ID with vaccines
The ID2020 Alliance has launched a new digital identity program at its annual summit in New York, in collaboration with the Government of Bangladesh, vaccine alliance Gavi, and new partners in government, academia, and humanitarian relief.
The program to leverage immunization as an opportunity to establish digital identity was unveiled by ID2020 in partnership with the Bangladesh Government’s Access to Information (a2i) Program, the Directorate General of Health Services, and Gavi, according to the announcement.
“We are implementing a forward-looking approach to digital identity that gives individuals control over their own personal information, while still building off existing systems and programs,” says Anir Chowdhury, policy advisor at a2i. “The Government of Bangladesh recognizes that the design of digital identity systems carries far-reaching implications for individuals’ access to services and livelihoods, and we are eager to pioneer this approach.”
Gavi CEO Seth Berkley says that 89 percent of children and adolescents who do not have identification live in countries where the organization is active. “We are enthusiastic about the potential impact of this program not just in Bangladesh, but as something we can replicate across Gavi-eligible countries, providing a viable route to closing the identity gap,” he says.
A partnership was also formed earlier this year between Gavi, NEC, and Simprints to use biometrics to improve vaccine coverage in developing nations.
“Digital ID is being defined and implemented today, and we recognize the importance of swift action to close the identity gap,” comments ID2020 Executive Director Dakota Gruener. “Now is the time for bold commitments to ensure that we respond both quickly and responsibly. We and our ID2020 Alliance partners, both present and future, are committed to rising to this challenge.”
ID2020 also announced new partnerships and provided progress reports on initiatives launched last year. Since last year’s summit, the ID2020 Alliance has been joined by the City of Austin, UC Berkeley’s CITRIS Policy Lab and Care USA.
The City of Austin, ID2020, and several other partners are working together with homeless people and the service providers who engage with them to develop a blockchain-enabled digital identity platform called MyPass to empower homeless people with their own identity data.
A pair of inaugural pilot programs launched last year in partnership with iRespond and Everest have each made progress, ID2020 says. The iRespond program has improved continuity of care for more than 3,000 refugees receiving treatment for chronic conditions from the International Rescue Committee in Thailand, according to the announcement, while Everest has assisted with the provision of access to critical energy subsidies and a range of additional services with secure and user-centric digital identities without relying on a smartphone.

The reason for studying the human iris is identification of a person. Albert Bertillon was the first person to notice this problem in the year 1880. He was a French physicist, who identified criminals by their irises.
In the year 1987, this problem was studied by Leonard Flom and Aran Safir. According to their patent [4], the iris is stable throughout the human life. All the features are quite stable in number and position except rare anomalies. It has been discovered that every iris is unique and no two people can have identical irises.

Many teachers and students in Nigerian institutions of learning find teaching and learning a herculean task and very boring because of the obsolete methods of teaching and learning in this sector of the Nigerian economy. New innovative and IT-driven approach will be used in this research to help improve the quality of teaching and learning in Nigerian schools. This research will try to find a solution to this problem, where both students and teachers will enjoy teaching and learning respectively in an environment where effective teaching and learning is the target objective.

user using his/her ID and fingerprints into a database after feature extraction. These features form a template that is used to determine the identity of the user, formulating the process of authentication. The enrolment process is carried out by an administrator of the attendance management system. During authentication, the biometrics of the user is captured again and the extracted features are compared with the ones already existing in the database to determine a match. After a successful match, attendance is marked against the user’s id used in matching the templates. The work utilized a fingerprint reader as the input to acquire images, developed program that has fingerprint recognition and identification system as well as database to store user’s information. The database comprises the fingerprint templates and other bio-data of the users together with the attendance records made by the users. Figure 1 shows the architecture of the proposed attendance management system.

Fingerprint-Based Attendance Management System (PDF Download Available). Available from: https://www.researchgate.net/publication/259973859_Fingerprint-Based_Attendance_Management_System [accessed May 16, 2017].

The field of Biometrics is an ever-expanding research area formed of different perceptions and theories from identity to verification. This can be fascinating with numerous aspects usually leading to authentication and security. Biometric identification involves capturing a physical element of an individual, which can be later used for verification by running multiple checks against stored data. It uses different methods to pattern match an individual and has always proven difficult to replicate. This is because each individual has a unique set of characteristics and no matching traits even in the case of identical twins. This research report presents an overview of various authorization and authentication techniques currently making use of biometrics technology. Moreover, a brief overview of biometric history is discussed to give an insight where it all began and how the use of technology has advanced its development. There is a variety of biometric authentication technologies used in today’s society, which are explored. One aspect to consider when deliberating about the use of biometric systems and how each application method has evolved is; at what point does the matter of security become an invasion of privacy?

Biometrics represents a return to a traditional way of identifying someone relying on what that person is instead of what that person knows or owns. Even though the significant amount of research that has been done in this field, there is still much to do as new emerging scenarios of application appear everyday. Biometric recognition systems are no longer restricted to forensic investigation or control management of employees. They have been gaining a visibility and applicability in daily use devices which reinforces their usability in all aspects of our day to day life. With this spread of biometric applications, nowadays commonly found in our laptops, our smart phones, some bank management services and airport custom services, a necessity for improved security also is rising. The importance of protecting our identity and our data has become crucial as our devices are filled with sensible information of many kinds. Therefore the presentation attack or liveness detection methods as countermeasures against spoofing attacks are more important than ever. New methods should be developed which address the new acquisition scenarios and which deal with the increased noise in the biometric data collected. Its of utmost importance to develop robust liveness detection methods. In particular, we worked on iris and fingerprint. These two biometric traits are very often chosen against others due to its characteristics. Among the objectives of this thesis were the purpose of making contributions in iris and fingerprint liveness detection proposing novel approaches whether from the imaging scenarios perspective, in the case of iris, or from the classification approach, in the case of fingerprint. Contributions were made regarding both traits, that exceeded the state-of-the art and resulted in both conferences and journal publications. Not only the spoofing attacks concern the biometric researchers but also the ability of the methods to deal with the noisy data. Therefore, the development of robust methods that overcome the compromised quality of data is a necessity of biometric research of nowadays. Therefore, another objective was to contribute to the fingerprint recognition problem developing robust methods to minutiae extraction. The work developed resulted in a proposed method for fingerprint orientation map estimation and a fingerprint image enhancement that over performed existing ones. This work aimed and succeeded to propose robust and realistic methods in both the iris and fingerprint liveness detection problem as well as in some steps of fingerprint recognition. It has to be noted that the focus of attention of this work was the quality of data and not the computational efficiency, therefore this one should have to be addressed if an application of the proposed methods to a real-world scenario was aimed. Another objective was to create new databases and promote common platforms of evaluation of methods such as biometric competitions. Therefore, along the work developed, two biometric databases were constructed and two biometric competitions were organized. Both databases had a strong impact in the research community and they continue to be disseminated. Publications using these benchmark datasets are numerous and continue to appear regularly.

As there is a rapid increase in technology development increase in identity theft, consumer fraud, threat to personal data also increasing day by day. The methods developed earlier to secure personal information from theft were not efficient and safe. Biometrics were introduced when there was a need of technology to secure personal information more efficiently. The old fashioned traditional approaches such as Personal Identification Number(PIN), passwords, keys, login id can be forgotten, stolen or lost. In biometric authentication system, a user does not need to remember any passwords or carry any keys. Like humans recognize each other by physical appearance and behavioural characteristics biometric systems makes use of physical characteristics like fingerprints, facial recognition, iris recognition to distinguish between a genuine user and an impostor. Initially biometric identification methods were developed to enhance security in government and corporate sectors, but nowadays it has made its way to almost all the private sectors like Banking. Finance, Home safety and security, Healthcare, Commercial safety and security etc. Since biometrics samples and templates of a biometric system which has single biometric feature to recognize a user can be replaced and duplicated, a new idea of fusion of multiple biometric identification technology has been introduced called multi modal biometric recognition systems which makes use of two or more biometric characteristics of an individual to identify as a genuine user or not.

El aumento y diversificación del uso de dispositivos móviles ha favorecido la experiencia del usuario con diferentes plataformas digitales, desde actividades básicas como el envío de mensajes, llamadas telefónicas, tomar fotos hasta el uso de redes sociales, correo electrónico, administración de cuentas bancarias y compras son sólo algunos de los ejemplos de las tareas que diariamente se realizan desde el móvil; las cuales hacen indispensable la seguridad de la información almacenada; por lo tanto, mantener su privacidad se convirtió en un punto focal en el desarrollo de los dispositivos móviles. En este artículo se presenta una investigación sobre el impacto que han cobrado los dispositivos móviles en la vida de las personas y la presencia de los sistemas biométricos en este tipo de aparatos, principalmente, como mecanismo de seguridad. Se examinaron  trabajos relacionados con la biometría en los dispositivos móviles con el propósito de conocer cuáles son los dispositivos que cuentan con sistemas biométricos integrados; además de identificar los rasgos biométricos utilizados para autenticar a las personas y para qué plataformas móviles fueron creados. Se encontró que el teléfono inteligente es el dispositivo que más cuenta con un sistema biométrico y que la huella dactilar es la característica más empleada, además de que el sistema operativo Android es la plataforma móvil más usada para estos fines.

This thesis presents a novel liveness detection method that exploits the acquisition workflow for iris biometrics on smart phones using a hybrid visible (RGB)/near infra-red (NIR) sensor. These devices are  able to capture both RGB and NIR images of the eye and iris region in synchronization. This multi-spectral information is mapped into a discrete feature space. An intermediate classifier which uses a distance metric close to Jenson-Shannon divergence is employed to classify the incoming image. Further, a fast, multi-frame pupil localization technique using one dimensional processing of the eye region is proposed and evaluated. This is used to analyze the pupil characteristics of the images classified as 'live' in the previous stage. It is shown that such an analysis could detect presentation attacks, even with a 3-D face model made of materials that has properties similar to human skin and the ocular region

Biometric systems are the systems those enable automatic individual recognition which is based on behavioral or physical features belonging to a specific individual. All the biometric features have their limits to an extent and no biometric system is flawless. Therefore, the unimodal biometric systems have a lot of drawbacks. To solve the mentioned inconvenience and limitations and to enhance the level of security the multimodal biometric systems are employed. Personal identification process is a very important process that resides a large portion of daily usages. Human is a rich subject having many features that can be used for identification purpose such as finger vein, iris, and face etc. Finger vein recognition is an encouraging biometric recognition technique; the verification of individuals is done on the basis of the vein patterns present in the fingers. Iris recognition has moved under more focus due to its high reliability and efficiency in personal identification in past few years. This paper discusses the advantages of multimodal biometric system over unimodal biometric system along with the fusion of traits using different techniques. It also discusses the techniques employed on finger vein and iris. Finally, future scope is presented for the possible work that can be done in the field of finger vein and iris.

https://sites.google.com/site/ijcsis/

Eye iris has been widely recognized as one of the strongest biometrics attributed to its high accuracy performance. However, templates in conventional iris recognition systems are unprotected and highly vulnerable to numerous security and privacy attacks. Despite a number of cancellable biometric schemes have been proposed but at the expense of substantially decreased accuracy performance. In this paper, we introduce a new cancellable iris scheme, coined as " Indexing-First-One " (IFO) hashing. IFO hashing is inspired from the Min-hashing that primarily used in text retrieval domain. However, IFO hashing has been further strengthened by two novel mechanisms, namely P-order Hadamard product and modulo threshold function. The IFO hashing scheme strikes the balance between accuracy performance and privacy/security protection. Comprehensive experiments on CASIA-v3 iris benchmark database and rigorous analysis demonstrate decent accuracy performance with respect to its original counterparts yet offer strong resilience against several major security and privacy attacks.

Przedstawiany felieton jest kontynuacją rozważań, przedstawionych wcześniej w tekście "Na ile bezpieczny jest Twój smartfon?", przedstawionym tydzień wcześniej także w Dzienniku Polskim i dostępnym także w serwisie Academia.edu. W prezentowanym tutaj tekście mowa jest głównie o zabezpieczeniach opartych na metodach biometrycznych: czytnikach linii papilarnych, urządzeniach rozpoznających twarz właściciela, a także metodach opartych na skanowaniu siatkówki oka.

—One of the potential passiveness in a biometric system is the invasion of stored biometric template, which may lead to serious security and privacy thefts. The emerging need of biometric approaches is evolved from privacy invasion and irrevocable issues of identity thefts as passwords and tokens can be easily compromised. To address these issues, the notion of cancelable biometrics is introduced to signify biometric templates that can be canceled and replaced with the inclusion of another independent authentication factor. Cancelable biometric generation technique based on randomized look-up table mapping has been proposed in this paper. The technique uses a decimal vector, which is evaluated from a row vector. Row vector is generated by applying 1-D Log Gabor filter on the raw iris template. The decimal vector is then mapped to look-up table based on the position of bits. The proposed approach enables an operation of cancelable iris biometric systems at a high security level. Experiments which are carried out on the CASIA V3 Interval iris database confirm the effectiveness of the proposed approach. Although, the accuracy of the proposed approach is confirmed as 94.26% but the approach is efficient if we consider the security and non-revocable perspectives.

7th International Conference on Data Mining & Knowledge Management (DaKM 2022) provides
a forum for researchers who address this issue and to present their work in a peer-reviewed forum.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in the
following areas, but are not limited to these topics only.

This paper is demonstrating to create a system of multifactor authentication based on biometric verification. Our system use iris for the first factor and fingerprint for the second factor. Once an attacker attempts to attack the system, there must have two factors. If one of them is compromised or broken, the attacker still has at least one more barrier to breach before successfully breaking into the target. Furthermore, this system will be implemented to enhance security for accessing control login government system.

For the traditional ATM terminal customer recognition systems only rely on bank cards, passwords, and such identity verification methods which measures are not perfect and functions are too single. For solving the bugs of traditional ones, using a Biological Technology in new ATM terminal customer recognition systems i.e., IRIS Biometrics Mechanism. A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Using iris recognition in ATM a customer simply walks up to the ATM and looks in a sensor camera to access their accounts. The camera instantly photographs the iris of the customer. If the customers iris data matches the record stored a database access is granted. At the ATM, A positive authentication can be read through glasses, contact lenses and most sunglasses. The performance of the system is evaluated by using the number of degrees of freedom, False Reject Rate (FRR), False Accept Rate (FAR), and Equal Error Rate (EER) and the metrics show that the proposed algorithm can be employed for an high protection human iris recognition system.

Face Recognition plays a major role in Biometrics. Feature selection is a measure issue in face recognition. This paper proposes a survey on face recognition. There are many methods to extract face features. In some advanced methods it can be extracted faster in a single scan through the raw image and lie in a lower dimensional space, but still retaining facial information efficiently. The methods which are used to extract features are robust to low-resolution images. The method is a trainable system for selecting face features. After the feature selection procedure next procedure is matching for face recognition. The recognition accuracy is increased by advanced methods.

Identifying attackers is a major apprehension to both organizations and governments. Recently, the most used applications for prevention or detection of attacks are intrusion detection systems. Biometrics technology is simply the measurement and use of the unique characteristics of living humans to distinguish them from one another and it is more useful as compare to passwords and tokens as they can be lost or stolen so we have choose the technique biometric authentication. The biometric authentication provides the ability to require more instances of authentication in such a quick and easy manner that users are not bothered by the additional requirements. In this paper, we have given a brief introduction about biometrics. Then we have given the information regarding the intrusion detection system and finally we have proposed a method which is based on fingerprint recognition which would allow us to detect more efficiently any abuse of the computer system that is running.

Iris recognition is a critical area of research in the field of security system and personal identification. In this paper, a novel, efficient technique for iris recognition is presented. The aim is to develop a lifting wavelet based algorithm. This method reduces the noise to the maximum extent possible, and extracts important information from the image. In this paper recognition is being done biorthogonal wavelet based method which is then compared with other wavelet family. The method was tested on the CASIA dataset of iris image. For matching the iris template Hamming Distance technique is used and checks the accuracy of the system. The present algorithm provides the 94.4% recognition rate and accuracy approx. 99 % on the CASIA iris data base version 1.

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Iris recognition is gaining a lot of popularity during recent years because of its large amount of universality,
acceptability, correctness and uniqueness. Due to its high reliability and nearby perfect recognition rates, iris recognition
is used in high security areas. In this paper, we have reviewed the various well known algorithms for iris recognition..
Daugman [5, 6, 7, 8], Wildes [11], Li Ma [9], and Tisse [2] are studied and compared based on their approaches. There are
four main stages in any iris recognition algorithm: segmentation, normalization, feature extraction, matching.

This paper details about segmentation of iris region
for iris recognition as a biometric personal identification and verification. Human iris is unique and differs from one
individual to another. Just as finger prints, biomedical proves
human irises are distinct. Also, iris can be easily accessed from any visual capturing device. The two dimensional structure of iris further assists the technology. This paper describes the extraction of iris region from an image of the human eye. The proposed algorithm defines a new method to segment Iris from the image. It’s a new technique for circular edge detection particularly for Iris recognition. An image undergoes various operations like black and white conversion, edge detection and filtering. The fact that the intensity of iris lies between the intensities of pupil and rest of the eye is the key here to extract iris. A simple vertical and horizontal scan is done over the image to get the tangents of the circles. A mathematical analysis is done on the images to get the radius and the center of the circle and hence the inner and outer circles of the iris are drawn or Hough transform can be done using the obtained values for more accuracy. We are constructed the circles after obtaining the values

The self-quotient image is a biologically inspired representation which has been proposed as an illumination invariant feature for automatic face recognition. Owing to the lack of strong domain specific assumptions underlying this representation, it can be readily extracted from raw images irrespective of the persons's pose, facial expression etc. What makes the self-quotient image additionally attractive is that it can be computed quickly and in a closed form using simple low-level image operations. However, it is generally accepted that the self-quotient is insufficiently robust to large illumination changes which is why it is mainly used in applications in which low precision is an acceptable compromise for high recall (e.g. retrieval systems). Yet, in this paper we demonstrate that the performance of this representation in challenging illuminations has been greatly underestimated. We show that its error rate can be reduced by over an order of magnitude, without any changes to the representation itself. Rather, we focus on the manner in which the dissimilarity between two self-quotient images is computed. By modelling the dominant sources of noise affecting the representation, we propose and evaluate a series of different dissimilarity measures, the best of which reduces the initial error rate of 63.0% down to only 5.7% on the notoriously challenging YaleB data set.

Face and iris are very common individual bio-metric features for person identification. Face recognition is the method of identification a person uniquely using face. Principal component analysis is one of the algorithms for face recognition. Iris recognition in another method of person identification using iris. Very popular iris recognition method is Daugman algorithm. Unimodal biometric system has various difficulties to detect a person like noisy and unusual data. Multimodal biometric system combined more than one individual modalities like face and iris to increase the efficiency. In this work, we combined principal component analysis and Daugman algorithm with ORL, YALE, CASIA and Real face dataset to combine face and iris recognition to improve the recognition efficiency.

IEEE˜ IEEE˜Abstract-Image quality assessment plays an important role in enhancing the performance of pattern recognition systems, including biometric systems. Although, quality assessment methods have been utilized for iris recognition on adults they have not been investigated on iris recognition for children. Iris recognition on children is difficult because of their uncooperative nature and may result in lower quality iris samples. In this study, we applied four existing quality assessment methods, light variation, pupil dilation, off-angle, and pixel count to data we collected from children and the CASIA database with iris images from adults. The results indicate that once the image without any visible iris area are removed, using an automated process, then the remaining images for children produces similar quality assessment distributions as those of iris images from adults. This study is the first step in creating an iris recognition system for children.

This paper is demonstrating to create a system of multifactor authentication based on biometric verification. Our system use iris for the first factor and fingerprint for the second factor. Once an attacker attempts to attack the system, there must have two factors. If one of them is compromised or broken, the attacker still has at least one more barrier to breach before successfully breaking into the target. Furthermore, this system will be implemented to enhance security for accessing control login government system.