A identificação pessoal através da análise da textura da íris é um método de identificação biométrico de grande eficiência. Algoritmos e técnicas foram desenvolvidos levando-se em consideração as características de textura da imagem da íris do olho humano. No entanto, essas características por serem estáticas são também susceptíveis a fraudes, ou seja, uma foto pode substituir a íris em análise. Por isso, este trabalho propõe um método para extrair as características de textura da íris durante a contração e dilatação da pupila, além das próprias características dinâmicas de contração e dilatação. Para isso foi desenvolvido um novo sistema de aquisição da imagem utilizando iluminação NIR (Near Infra-Red) e levando-se em conta o reflexo consensual dos olhos. As características são medidas de acordo com um padrão dinâmico de iluminação controlado pelo programa. Com isso, é possível aumentar a segurança de dispositivos de reconhecimento biométrico de pessoas através da íris, pois, somente íris vivas podem ser utilizadas. Os resultados mostram um índice de precisão significativo na capacidade de discriminação destas características. / The personal identification by iris texture analysis is a highly effective biometric identification method. Some algorithms and techniques were developed, taking into consideration the texture features of the iris image in the human eye. Nonetheless, such features, due to the fact that they are static, are also susceptible to fraud. That is, a picture can replace the iris in an analysis. For that reason, this work proposes a method for extracting texture features of the iris during the pupil contraction and dilation, in addition to the dynamic contraction and dilation features themselves. Therefore, it was developed a new image acquisition system through NIR (Near Infra-Red) illumination, considering the consensual reflex of the eyes. Features are measured according to a dynamic illumination standard controlled by the software and are afterwards selected by means of data mining. Then it is possible to increase the safety in the biometric recognition devices of people through their iris, since only living irises can be utilized. Results show a significant precision index in determining such features.

A identificação pessoal através da análise da textura da íris é um método de identificação biométrico de grande eficiência. Algoritmos e técnicas foram desenvolvidos levando-se em consideração as características de textura da imagem da íris do olho humano. No entanto, essas características por serem estáticas são também susceptíveis a fraudes, ou seja, uma foto pode substituir a íris em análise. Por isso, este trabalho propõe um método para extrair as características de textura da íris durante a contração e dilatação da pupila, além das próprias características dinâmicas de contração e dilatação. Para isso foi desenvolvido um novo sistema de aquisição da imagem utilizando iluminação NIR (Near Infra-Red) e levando-se em conta o reflexo consensual dos olhos. As características são medidas de acordo com um padrão dinâmico de iluminação controlado pelo programa. Com isso, é possível aumentar a segurança de dispositivos de reconhecimento biométrico de pessoas através da íris, pois, somente íris vivas podem ser utilizadas. Os resultados mostram um índice de precisão significativo na capacidade de discriminação destas características. / The personal identification by iris texture analysis is a highly effective biometric identification method. Some algorithms and techniques were developed, taking into consideration the texture features of the iris image in the human eye. Nonetheless, such features, due to the fact that they are static, are also susceptible to fraud. That is, a picture can replace the iris in an analysis. For that reason, this work proposes a method for extracting texture features of the iris during the pupil contraction and dilation, in addition to the dynamic contraction and dilation features themselves. Therefore, it was developed a new image acquisition system through NIR (Near Infra-Red) illumination, considering the consensual reflex of the eyes. Features are measured according to a dynamic illumination standard controlled by the software and are afterwards selected by means of data mining. Then it is possible to increase the safety in the biometric recognition devices of people through their iris, since only living irises can be utilized. Results show a significant precision index in determining such features.

<p>This master thesis evaluates the use of off-the-shelf standard cameras for biometric identification of the human iris. As demands on secure identification are constantly rising and as the human iris provides with a pattern that is excellent for identification, the use of inexpensive equipment could help iris recognition become a new standard in security systems. To test the performance of such a system a review of the current state of the research in the area was done and the most promising methods were chosen for evaluation. A test environment based on open source code was constructed to measure the performance of iris recognition methods, image quality and recognition rate.</p><p>In this paper the image quality of a database consisting of images from a standard camera is assessed, the most important problem areas identified, and the overall recognition performance measured. Iris recognition methods found in literature are tested on this class of images. These together with newly developed methods show that a system using standard equipment can be constructed. Tests show that the performance of such a system is promising.</p>

Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.

In this thesis, person identification by combining automatic face and iris recognition is analyzed. Person identification by his face is one of the most intuitive from all biometric measures. We are used to recognizing familiar faces and confirming identity by a short glance at one's id card which contains image of the face. We are also used to being observed by surveillance cameras, which can perform biometric authentication without even being noticed. However, facial biometrics is one of most unstable metrics because the face gets noticeably older in several years and can frequently change depending on the mood of its owner. The core algorithm for facial recognition presented in this work is based on Gabor features. Deep analysis of each step helped to develop the method with better or similar accuracy to the best published results received on the same datasets, while being simple and fast. On the other hand, person identification by his iris is one of the most sophisticated, stable and accurate biometrics. The core algorithm for iris recognition presented in this work is based on a novel iris texture representation by local extremum points of multiscale Taylor expansion. The proposed irises comparison method is very different from the classic phase-based methods, but is also fast and accurate. Combining it with our implementation of phase-based method results in superior recognition accuracy which is comparable or better than any published results received on the same... [to full text] / Darbe tyrinėjama asmens identifikacija, kombinuojant automatinį veido ir akies rainelės atpažinimą. Automatinė identifikacija pagal veidą yra intuityviausia iš biometrijos metrikų, kadangi būtent pagal veidą mes geriausiai sugebame atpažinti pažįstamus asmenis. Tai yra ir viena labiausiai priimtinų, kadangi visi esame įprate, kad mus filmuoja apsaugos kameros, lengviausiai išmatuojama - nes nereikalauja jokių įmantrių skanerių, tačiau kartu - tai yra ir viena iš nestabiliausių metrikų, kadangi veidas sensta ir šiaip kinta priklausomai nuo savininko nuotaikos. Darbe pristatomas veidų atpažinimo algoritmas paremtas Gaboro požymiais. Nuodugni analizė padėjo sukurti algoritmą, kurio tikslumą vertinant standartiniais testais jis lenkia arba yra lygus su geriausiais publikuotais metodais, tačiau pasižymi paprastumu ir dideliu greičiu. Tuo tarpu automatinė identifikacija pagal rainelę yra laikoma viena stabiliausių ir tiksliausių. Darbe pristatomas rainelių atpažinimo algoritmas naudoja naujovišką rainelių tekstūros vaizdavimo būdą, paremtą lokaliais dvimačiais funkcijų aproksimacijos Teiloro eilutėmis ekstremumais. Kartu pristatomas naudojamų požymių palyginimo metodas, kuris yra labai nutolęs nuo bet kokių iki šiol rainelių tekstūrų palyginimui naudojamų metodų. Pasiūlytas rainelių atpažinimo metodas vėlgi yra spartus ir itin tikslus, o sujungus su klasikinio stiliaus rainelių tekstūrų palyginimu tikslumu nenusileidžia geriausiems publikuotiems metodams. Darbas užbaigiamas veidų... [toliau žr. visą tekstą]

Darbe tyrinėjama asmens identifikacija, kombinuojant automatinį veido ir akies rainelės atpažinimą. Automatinė identifikacija pagal veidą yra intuityviausia iš biometrijos metrikų, kadangi būtent pagal veidą mes geriausiai sugebame atpažinti pažįstamus asmenis. Tai yra ir viena labiausiai priimtinų, kadangi visi esame įprate, kad mus filmuoja apsaugos kameros, lengviausiai išmatuojama - nes nereikalauja jokių įmantrių skanerių, tačiau kartu - tai yra ir viena iš nestabiliausių metrikų, kadangi veidas sensta ir šiaip kinta priklausomai nuo savininko nuotaikos. Darbe pristatomas veidų atpažinimo algoritmas paremtas Gaboro požymiais. Nuodugni analizė padėjo sukurti algoritmą, kurio tikslumą vertinant standartiniais testais jis lenkia arba yra lygus su geriausiais publikuotais metodais, tačiau pasižymi paprastumu ir dideliu greičiu. Tuo tarpu automatinė identifikacija pagal rainelę yra laikoma viena stabiliausių ir tiksliausių. Darbe pristatomas rainelių atpažinimo algoritmas naudoja naujovišką rainelių tekstūros vaizdavimo būdą, paremtą lokaliais dvimačiais funkcijų aproksimacijos Teiloro eilutėmis ekstremumais. Kartu pristatomas naudojamų požymių palyginimo metodas, kuris yra labai nutolęs nuo bet kokių iki šiol rainelių tekstūrų palyginimui naudojamų metodų. Pasiūlytas rainelių atpažinimo metodas vėlgi yra spartus ir itin tikslus, o sujungus su klasikinio stiliaus rainelių tekstūrų palyginimu tikslumu nenusileidžia geriausiems publikuotiems metodams. Darbas užbaigiamas veidų... [toliau žr. visą tekstą] / In this thesis, person identification by combining automatic face and iris recognition is analyzed. Person identification by his face is one of the most intuitive from all biometric measures. We are used to recognizing familiar faces and confirming identity by a short glance at one's id card which contains image of the face. We are also used to being observed by surveillance cameras, which can perform biometric authentication without even being noticed. However, facial biometrics is one of most unstable metrics because the face gets noticeably older in several years and can frequently change depending on the mood of its owner. The core algorithm for facial recognition presented in this work is based on Gabor features. Deep analysis of each step helped to develop the method with better or similar accuracy to the best published results received on the same datasets, while being simple and fast. On the other hand, person identification by his iris is one of the most sophisticated, stable and accurate biometrics. The core algorithm for iris recognition presented in this work is based on a novel iris texture representation by local extremum points of multiscale Taylor expansion. The proposed irises comparison method is very different from the classic phase-based methods, but is also fast and accurate. Combining it with our implementation of phase-based method results in superior recognition accuracy which is comparable or better than any published results received on the same... [to full text]

Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Neste trabalho é estudada a viabilidade de uma implementação em paralelo do algoritmo scale invariant feature transform (SIFT) para identificação de íris. Para a implementação do código foi utilizada a arquitetura para computação paralela compute unified device architecture (CUDA) e a linguagem OpenGL shading language (GLSL). O algoritmo foi testado utilizando três bases de dados de olhos e íris, o noisy visible wavelength iris image Database (UBIRIS), Michal-Libor e CASIA. Testes foram feitos para determinar o tempo de processamento para verificação da presença ou não de um indivíduo em um banco de dados, determinar a eficiência dos algoritmos de busca implementados em GLSL e CUDA e buscar valores de calibração que melhoram o posicionamento e a distribuição dos pontos-chave na região de interesse (íris) e a robustez do programa final. / Present work studies the feasibility of a parallel implementation of the scene recognition algorithm SIFT for iris recognition. The code was built using the Compute Unified Device Architecture (CUDA) and the shading language GLSL. The algorithm was tested using three databases containing eyes and iris, the UBIRIS, Michal- Libor and CASIA. Tests were made for: analyzing the requested time for checking if an subject is or is not present on current database, the efficiency of the search algorithms written in CUDA and GLSL, the search for calibration values that improve keypoints position and distribution through the region of interest (iris), analyzing the reliability of the final code.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Neste trabalho é estudada a viabilidade de uma implementação em paralelo do algoritmo scale invariant feature transform (SIFT) para identificação de íris. Para a implementação do código foi utilizada a arquitetura para computação paralela compute unified device architecture (CUDA) e a linguagem OpenGL shading language (GLSL). O algoritmo foi testado utilizando três bases de dados de olhos e íris, o noisy visible wavelength iris image Database (UBIRIS), Michal-Libor e CASIA. Testes foram feitos para determinar o tempo de processamento para verificação da presença ou não de um indivíduo em um banco de dados, determinar a eficiência dos algoritmos de busca implementados em GLSL e CUDA e buscar valores de calibração que melhoram o posicionamento e a distribuição dos pontos-chave na região de interesse (íris) e a robustez do programa final. / Present work studies the feasibility of a parallel implementation of the scene recognition algorithm SIFT for iris recognition. The code was built using the Compute Unified Device Architecture (CUDA) and the shading language GLSL. The algorithm was tested using three databases containing eyes and iris, the UBIRIS, Michal- Libor and CASIA. Tests were made for: analyzing the requested time for checking if an subject is or is not present on current database, the efficiency of the search algorithms written in CUDA and GLSL, the search for calibration values that improve keypoints position and distribution through the region of interest (iris), analyzing the reliability of the final code.

This master thesis evaluates the use of off-the-shelf standard cameras for biometric identification of the human iris. As demands on secure identification are constantly rising and as the human iris provides with a pattern that is excellent for identification, the use of inexpensive equipment could help iris recognition become a new standard in security systems. To test the performance of such a system a review of the current state of the research in the area was done and the most promising methods were chosen for evaluation. A test environment based on open source code was constructed to measure the performance of iris recognition methods, image quality and recognition rate. In this paper the image quality of a database consisting of images from a standard camera is assessed, the most important problem areas identified, and the overall recognition performance measured. Iris recognition methods found in literature are tested on this class of images. These together with newly developed methods show that a system using standard equipment can be constructed. Tests show that the performance of such a system is promising.