A new report by computer scientists at the National Institute of Standards and Technology (NIST) demonstrates that iris recognition algorithms can maintain their accuracy, affirming their potential for large-scale identity management applications. Examples include the federal Personal Identity Verification program, cyber security, and counterterrorism.
After fingerprints, iris recognition has emerged in recent years as the second most widely supported biometric characteristic. This requires images to be captured in a standard format and prepared so that they are compact enough for a smart card and for transmission across global networks. The images also have to be identifiable by computer algorithms and interoperable with any iris-matcher product regardless of the manufacturer.
NIST established the Iris Exchange IREX program as a NIST-industry collaboration to encourage development of iris recognition algorithms operating on images conforming to the new standard. The first IREX project, IREX I, provided quantitative support to the standard by conducting the largest independently administered test of iris recognition technology to date. The test attracted 19 recognition technologies from 10 different providers.
The IREX I tests also looked at technical factors affecting users. These include speed-accuracy tradeoffs, threshold calibration, storage requirements, image quality assessment, and the effects of iris size, eyelid occlusion and pupil dilation. The test result shows that forensic applications, where image quality is sometimes degraded, can benefit from slower but more powerful algorithms.
Plans for IREX II are under way to calibrate and evaluate the effectiveness and efficiency of iris image quality assessment algorithms. This study will support a new international iris image quality standard by identifying specific iris image properties that are influential on recognition accuracy.
2 comments:
Three aspects of this review that I thought were presented particularly well include the details that Meghan incorporated. Also, the article was very clear and easy to understand, since she explained it very well. Also, I liked that she explained how the iris recognition algorithm works. Some suggestions are that she could have added her own opinion about the new report. Also, she could have gone into further detail regaurding the conclusion and what they plan to do. Overall, I really liked this article, as I learned many new things about the NIST.
Meghan summarized the article, "Test Proves 'The Eyes Have it' For ID Verification". This article was interesting because of all the details included. Another good aspect of this review is that instead of just stating what certain eye processes were, iris recognition algorithm, she explained how the function worked. The article was easy to follow too. To make the article better, she could have elaborated on future plans with this process. Also, hearing her own opinions would have made it easier to figure out if there was bias in the summary. I learned from this article that there are so many ways to identify a person, besides DNA.
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