Indiana University-Purdue University Indianapolis (IUPUI) / Biometrics identi es/veri es a person using his/her physiological or behavioral characteristics. It is becoming an important ally for law enforcement and homeland security. Among all the biometric modalities, iris is tested to be the most accurate one. However, most existing methods are not designed for non-cooperative users and cannot work with o -angle or low quality iris images. In this thesis, we propose a robust multi-stage feature extraction and matching approach for non-cooperative iris recognition. We developed the SURF-like method to extract stable feature points, used Gabor Descriptor method for local feature description, and designed the multi- stage feature extraction and matching scheme to improve the recognition accuracy and speed. The related experimental results show that the proposed method is very promising. In addition, two template security enhanced schemes for the proposed non- cooperative iris recognition are introduced. The related experimental results show that these two schemes can e ectively realize cancelability of the enrolled biometric templates while at the same time achieving high accuracy.

Made available in DSpace on 2016-06-02T19:05:57Z (GMT). No. of bitstreams: 1 4427.pdf: 8518956 bytes, checksum: 0179ef9750c36082852192a44b3e6834 (MD5) Previous issue date: 2012-06-14 / Financiadora de Estudos e Projetos / The identification of humans by their iris structure has been explored since 1993, when the first algorithm was made available by John Daugman. Since then, iris recognition systems are widely used for access control of several kinds of environments. Such systems typically requires the user´s cooperation, appropriate lighting conditions, and images obtained in the infra-red band. Dynamic methods for biometric identification has been the subject of studies in the past few years, including iris recognition in non-cooperative environments. This paper proposes a pre-processing methodology to enable iris images classification taken in a noncooperative setting, from users at a certain distance, or while moving. The methodology aims to select images from the visible band containing an acceptable level of noise, and as such being suitable to apply the classification algorithms. Experimental results have shown that images with up to 40% of noise can still be used, suggesting the methodology may be useful as an aid to implement iris recognition systems at distance or in motion. / A identificação de seres humanos pela estrutura da íris vem sendo explorada desde 1993, quando foi disponibilizado o primeiro algoritmo por John Daugman. Desde então, os sistemas de reconhecimento de íris são amplamente utilizados para o controle de acesso de diversas aplicações. Tais sistemas normalmente, requerem a cooperação do usuário, condições de iluminações adequadas, e imagens obtidas na banda infravermelha. Métodos dinâmicos para identificação biométrica tem sido objeto de estudo nos últimos anos, incluindo o reconhecimento de íris em ambientes não cooperativos. Este trabalho propõe uma metodologia de pré-processamento da imagens da íris para classificação de amostras capturadas de forma não cooperativa, a uma certa distância, ou em movimento pelo usuário. A metodologia visa selecionar imagens a partir da banda visível contendo um nível de ruído aceitável, de forma que possa ser eficaz na aplicação dos algoritmos de classificação. Resultados experimentais demostraram que imagens com até 40% de ruído podem ainda ser utilizadas, sugerindo a utilização da metodologia como um auxílio para implementação de sistemas de reconhecimento de íris à distância ou em movimento.