Identificazione dei parametri retinici per l'autenticazione utente

In questa tesi si è voluto studiare e implementare una soluzione all’avanguardia per quanto riguarda il riconoscimento biometrico. Fino ad ora sono stati valutati dei metodi abbastanza veloci in fase di scannarizzazione del soggetto ed elaborazione del modello in esame. Essi risultano essere abbastanza affidabili; tuttavia alcuni sono considerati poco sicuri (impronte digitali o connotati del viso) nella fase di autenticazione dell’utente. Questo perchè tramite chirurgia è possibile modificare fisicamente alcune caratteristiche dell’individuo. L’identificazione retinica è un argomento tutt’altro che nuovo, ma nonostante ciò le prime applicazioni pratiche sono state presentate poco tempo fa. Sicuramente ci sono aspetti negativi derivanti dall’utilizzo di questa tecnica; l’utente infatti preferirebbe interagire con strumenti che non debbano stare a contatto con i propri occhi. Il paper cui si ha fatto riferimento è intitolato ’A Novel Retinal Identification System’ ed è stato pubblicato il 21 Febbraio 2008. Il sistema illustrato in tale paper è composto da tre moduli principali che includono la segmentazione dei vasi sanguigni, la generazione di caratteristiche e il pattern matching finale. La ricerca in questa direzione è esplosa questi ultimi anni e sicuramente in futuro ulteriori modelli più efficienti e sicuri verranno a galla

A Review: Person Identification using Retinal Fundus Images

In this paper a review on biometric person identification has been discussed using features from retinal fundus image. Retina recognition is claimed to be the best person identification method among the biometric recognition systems as the retina is practically impossible to forge. It is found to be most stable, reliable and most secure among all other biometric systems. Retina inherits the property of uniqueness and stability. The features used in the recognition process are either blood vessel features or non-blood vessel features. But the vascular pattern is the most prominent feature utilized by most of the researchers for retina based person identification. Processes involved in this authentication system include pre-processing, feature extraction and feature matching. Bifurcation and crossover points are widely used features among the blood vessel features. Non-blood vessel features include luminance, contrast, and corner points etc. This paper summarizes and compares the different retina based authentication system. Researchers have used publicly available databases such as DRIVE, STARE, VARIA, RIDB, ARIA, AFIO, DRIDB, and SiMES for testing their methods. Various quantitative measures such as accuracy, recognition rate, false rejection rate, false acceptance rate, and equal error rate are used to evaluate the performance of different algorithms. DRIVE database provides 100\% recognition for most of the methods. Rest of the database the accuracy of recognition is more than 90\%

Privacy in Biometric Systems

Biometrics are physiological and/or behavioral characteristics of a person that have been used to provide an automatic proof of identity in a growing list of applications including crime/terrorism fighting, forensics, access and border control, securing e-/m-commerce transactions and service entitlements. In recent years, a great deal of research into a variety of new and traditional biometrics has widened the scope of investigations beyond improving accuracy into mechanisms that deal with serious concerns raised about the potential misuse of collected biometric data. Despite the long list of biometrics’ benefits, privacy concerns have become widely shared due to the fact that every time the biometric of a person is checked, a trace is left that could reveal personal and confidential information. In fact, biometric-based recognition has an inherent privacy problem as it relies on capturing, analyzing, and storing personal data about us as individuals. For example, biometric systems deal with data related to the way we look (face, iris), the way we walk (gait), the way we talk (speaker recognition), the way we write (handwriting), the way we type on a keyboard (keystroke), the way we read (eye movement), and many more. Privacy has become a serious concern for the public as biometric systems are increasingly deployed in many applications ranging from accessing our account on a Smartphone or computer to border control and national biometric cards on a very large scale. For example, the Unique Identification Authority of India (UIDAI) has issued 56 million biometric cards as of January 2014 [1], where each biometric card holds templates of the 10 fingers, the two irises and the face. An essential factor behind the growing popularity of biometrics in recent years is the fact that biometric sensors have become a lot cheaper as well as easier to install and handle. CCTV cameras are installed nearly everywhere and almost all Smartphones are equipped with a camera, microphone, fingerprint scanner, and probably very soon, an iris scanner

Retina Recognition Using Crossings and Bifurcations

Recognition of people on the basis of biometric characteristics has been known for many centuries. One of the most used biometric features is fingerprint. Recently, we have also come across the iris pattern more often. Retinal recognition offers similarly reliable mechanisms, but they are not yet well explored. Our procedure for obtaining a biometric pattern is partly based on fingerprints. In comparison with fingerprints, retinal recognition identifies bifurcations or optical crossings, i.e., instead of papillary lines, the vessels are used. The procedure is more complicated due to the multiple layers in which the blood vessels intersect. Our work deals with determining the probabilities for various areas of the retina in which bifurcation and crossing occur. It also describes how recognition can be affected by various diseases

Design of Optoelectronic System for Measuring and Evaluating the Relative Positions of the Eye and Sights

Tato diplomová práce je zaměřena na experimentálním měření a vyhodnocování vzájemné polohy oka a mířidel vzduchové pušky, respektive kamer. Problematika biometrické identifikace oka je hojně využívána v mnoha odvětví a v kombinaci s poznatky získanými v rámci této diplomové práce může být jmenovaná problematiky dále rozvíjena. Diplomová práce v teoretické části pojednává zejména o anatomii lidského oka a sportovní střelbě, neboť do této oblasti jsou výstupy práce směřovány. V praktické části práce je popsán výběr kamer, jejich umístění a velmi důležitý proces kalibrování. Následně je popsán navržený algoritmus pro detekci očního okolí, středu zornice a detekce kružnic zornice a duhovky. Součástí této práce je i navržení a popsání algoritmu pro detekci natočení oka v oční jamce vztažené k optické ose mířidel, respektive páru kamer. Experimentálně získaná data jsou zaznamenána a zpracována ve formě grafických výstupů a v závěr práce jsou dosažené výsledky diskutovány.This diploma thesis deals with experimental measurement and evaluation of the mutual position of human eye and the air rifle sights, or more precisely, the video cameras. The issue of biometrical identification of an eye is commonly employed in various fields and combined with the results presented in this thesis, the issues can be further developed. The theoretical part of the thesis introduces the basic concepts of the research, focusing primarily on the anatomy of human eye and describing shooting sport. The practical part describes the selection of video cameras, their location and the very important process of calibration. It also presents the proposed algorithm for detecting the eye area, pupil centre and detection of the pupil and iris circle. Another part of the thesis is the proposal and description of the algorithm for detecting the rotation of an eye in the eye socket related to the optical axis of the sights, or, more precisely, the cameras. The experimentally collected data are recorded and processed in the form of graphical outputs and the results are then discussed at the very end of the thesis.450 - Katedra kybernetiky a biomedicínského inženýrstvídobř

Advancing the technology of sclera recognition

PhD ThesisEmerging biometric traits have been suggested recently to overcome some challenges and issues related to utilising traditional human biometric traits such as the face, iris, and fingerprint. In particu- lar, iris recognition has achieved high accuracy rates under Near- InfraRed (NIR) spectrum and it is employed in many applications for security and identification purposes. However, as modern imaging devices operate in the visible spectrum capturing colour images, iris recognition has faced challenges when applied to coloured images especially with eye images which have a dark pigmentation. Other issues with iris recognition under NIR spectrum are the constraints on the capturing process resulting in failure-to-enrol, and degradation in system accuracy and performance. As a result, the research commu- nity investigated using other traits to support the iris biometric in the visible spectrum such as the sclera. The sclera which is commonly known as the white part of the eye includes a complex network of blood vessels and veins surrounding the eye. The vascular pattern within the sclera has different formations and layers providing powerful features for human identification. In addition, these blood vessels can be acquired in the visible spectrum and thus can be applied using ubiquitous camera-based devices. As a consequence, recent research has focused on developing sclera recog- nition. However, sclera recognition as any biometric system has issues and challenges which need to be addressed. These issues are mainly related to sclera segmentation, blood vessel enhancement, feature ex- traction, template registration, matching and decision methods. In addition, employing the sclera biometric in the wild where relaxed imaging constraints are utilised has introduced more challenges such as illumination variation, specular reflections, non-cooperative user capturing, sclera blocked region due to glasses and eyelashes, variation in capturing distance, multiple gaze directions, and eye rotation. The aim of this thesis is to address such sclera biometric challenges and highlight the potential of this trait. This also might inspire further research on tackling sclera recognition system issues. To overcome the vii above-mentioned issues and challenges, three major contributions are made which can be summarised as 1) designing an efficient sclera recognition system under constrained imaging conditions which in- clude new sclera segmentation, blood vessel enhancement, vascular binary network mapping and feature extraction, and template registra- tion techniques; 2) introducing a novel sclera recognition system under relaxed imaging constraints which exploits novel sclera segmentation, sclera template rotation alignment and distance scaling methods, and complex sclera features; 3) presenting solutions to tackle issues related to applying sclera recognition in a real-time application such as eye localisation, eye corner and gaze detection, together with a novel image quality metric. The evaluation of the proposed contributions is achieved using five databases having different properties representing various challenges and issues. These databases are the UBIRIS.v1, UBIRIS.v2, UTIRIS, MICHE, and an in-house database. The results in terms of segmen- tation accuracy, Equal Error Rate (EER), and processing time show significant improvement in the proposed systems compared to state- of-the-art methods.Ministry of Higher Education and Scientific Research in Iraq and the Iraqi Cultural Attach´e in Londo