Evaluating the information content of near-infrared iris imagery
| Autor: | Hau Ngo, Robert W. Ives, Stephen D. Winchell |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Biometrics
urogenital system Computer science business.industry fungi Iris recognition Near-infrared spectroscopy Pattern recognition urologic and male genital diseases female genital diseases and pregnancy complications Identification (information) medicine.anatomical_structure Content (measure theory) medicine Computer vision cardiovascular diseases Artificial intelligence Iris (anatomy) business Recognition algorithm |
| Zdroj: | ISABEL |
| DOI: | 10.1145/2093698.2093846 |
| Popis: | The human iris exhibits random and unique textural patterns that allow for identification with high accuracy. These patterns are evident in near-infrared (NIR) imagery, even for very dark irises. The authors investigate the information content of the iris contained in these patterns, and how it affects recognition performance. In this paper, iris templates are created from NIR iris imagery with the Ridge Energy Direction (RED) recognition algorithm, and using common biometric performance metrics we determine which portions of the iris contain the most distinctive information for recognition. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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