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Ordinal Measures for Iris Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009Images of a human iris contain rich texture information useful for identity authentication. A key and still open issue in iris recognition is how best to represent such textural information using a compact set of features (iris features). In this paper, we propose using ordinal measures for iris feature representation with the objective of ...
Zhenan Sun, Tieniu Tan
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IEEE Transactions on Dependable and Secure Computing, 2018
Elements of a person's biometrics are typically stable over the duration of a lifetime, and thus, it is highly important to protect biometric data while supporting recognition (it is also called secure biometric recognition). However, the biometric data that are derived from a person usually vary slightly due to a variety of reasons, such as distortion
Dongdong Zhao 0001 +3 more
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Elements of a person's biometrics are typically stable over the duration of a lifetime, and thus, it is highly important to protect biometric data while supporting recognition (it is also called secure biometric recognition). However, the biometric data that are derived from a person usually vary slightly due to a variety of reasons, such as distortion
Dongdong Zhao 0001 +3 more
openaire +1 more source
Parallelizing Iris Recognition
IEEE Transactions on Information Forensics and Security, 2009Iris recognition is one of the most accurate biometric methods in use today. However, the iris recognition algorithms are currently implemented on general purpose sequential processing systems, such as generic central processing units (CPUs). In this work, we present a more direct and parallel processing alternative using field-programmable gate arrays
Ryan N. Rakvic +4 more
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2016 IEEE International Conference on Image Processing (ICIP), 2016
Despite significant advances in iris recognition (IR), the efficient and robust IR at scale and in non-ideal conditions presents serious performance issues and is still ongoing research topic. Deep Convolution Neural Networks (DCNN) are powerful visual models that have reported state-of-the-art performance in several domains.
Abhishek Kumar Gangwar, Akanksha Joshi
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Despite significant advances in iris recognition (IR), the efficient and robust IR at scale and in non-ideal conditions presents serious performance issues and is still ongoing research topic. Deep Convolution Neural Networks (DCNN) are powerful visual models that have reported state-of-the-art performance in several domains.
Abhishek Kumar Gangwar, Akanksha Joshi
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Iris Recognition for Iris Tilted in Depth
2003The capability of conducting unconscious recognition, in the sense of identifying people without them knowing it, is increasingly important in security and surveillance applications. Iris recognition is one of the few biometric recognition technologies that could serve the purpose.
Chun-Nam Chun, Ronald Chung
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An Iris Segmentation Procedure for Iris Recognition
2004Iris segmentation is a critical stage in the whole iris recognition process In this paper, a procedure of iris segmentation is presented which was designed on the basis of the natural properties of the iris The proposed procedure consists of two main steps: circles localization and non-iris region detection In our method, we took into consideration of ...
Xiaoyan Yuan, Pengfei Shi
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Iris Recognition at a Distance
2005We describe experiments demonstrating the feasibility of human iris recognition at up to 10 m distance between subject and camera. The iris images of 250 subjects were captured with a telescope and infrared camera, while varying distance, capture angle, environmental lighting, and eyewear.
Craig L. Fancourt +6 more
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6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07), 2007
The authentication of people using iris-based recognition is a widely developing technology. Iris recognition is feasible for use in differentiating between identical twins. Though the iris color and the overall statistical quality of the iris texture may be dependent on genetic factors, the textural details are independent and uncorrelated for ...
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The authentication of people using iris-based recognition is a widely developing technology. Iris recognition is feasible for use in differentiating between identical twins. Though the iris color and the overall statistical quality of the iris texture may be dependent on genetic factors, the textural details are independent and uncorrelated for ...
openaire +1 more source