Relaxing the constraints on image capture for iris recognition systems

Peter A. Smith; John M. Rickman; Jeremy W Hartsell

doi:10.1117/12.919881

4 May 2012 Relaxing the constraints on image capture for iris recognition systems

Peter A. Smith, John M. Rickman, Jeremy W Hartsell

Proceedings Volume 8371, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX; 83711P (2012) https://doi.org/10.1117/12.919881
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Iris recognition is considered to be one of the most accurate biometrics, but user inconvenience during the image acquisition phase has limited its widespread use. Image capture is largely constrained to well-controlled situations, where subjects must remain relatively stationary or within a capture "volume" close to the camera. As a consequence, iris recognition systems have a reputation for being borderline intrusive, and less friendly for both subjects and operators. To support the development of a more natural and acceptable iris capture system, we have sought to develop a pre-processor driven imaging system that predicts a maximal opportunity window for iris capture for a subject engaged in natural motion based on predictive head and eye movement algorithms. This paper describes a first-generation prototype iris capture system that utilizes this approach. A wide field of view camera is used to track a person's face and provide head pose data as input to the predictive algorithm. The algorithm is then used to direct a second narrow field of view camera to capture the iris image more reliably. This system serves as a platform for further development of head movement prediction algorithms used to enhance the probability of iris capture in moving or uncooperative subjects.

Citation Download Citation

Peter A. Smith, John M. Rickman, and Jeremy W Hartsell "Relaxing the constraints on image capture for iris recognition systems", Proc. SPIE 8371, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX, 83711P (4 May 2012); https://doi.org/10.1117/12.919881

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