Name
Abstract | ||
|---|---|---|
Iris recognition utilizes distinct patterns found in the human iris to perform identification. Image acquisition is a critical first step toward successful operation of iris recognition systems. However, the quality of iris images required by standard iris recognition algorithms puts stringent constraints on the imaging systems, which results in a constrained capture volume. We have incorporated adaptive optical elements to expand the capture volume of a 3-m stand-off iris recognition system. (c) 2012 SPIE and IS&T. [DOI: 10.1117/1.JEI.21.1.013004] |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1117/1.JEI.21.1.013004 | JOURNAL OF ELECTRONIC IMAGING |
Field | DocType | Volume |
Iris recognition,Computer vision,Pattern recognition,Computer science,Artificial intelligence | Journal | 21 |
Issue | ISSN | Citations |
1 | 1017-9909 | 1 |
PageRank | References | Authors |
0.35 | 6 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junoh Choi | 1 | 1 | 0.35 |
| Kevin R. Dixon | 2 | 1 | 0.69 |
| David V. Wick | 3 | 1 | 0.35 |
| Brett E. Bagwell | 4 | 1 | 0.35 |
| Grant H. Soehnel | 5 | 1 | 0.35 |
| Brian Clark | 6 | 1 | 0.35 |