Biometrics Bibliography - Revision history

Srmclare at 19:48, 26 November 2007

2007-11-26T19:48:30Z

Srmclare: /* Surveys */

2007-10-23T01:48:41Z

‎Surveys

Srmclare: /* Surveys */

2007-10-23T01:48:23Z

‎Surveys

Srmclare at 01:43, 23 October 2007

2007-10-23T01:43:06Z

Srmclare at 01:41, 23 October 2007

2007-10-23T01:41:03Z

Srmclare at 01:39, 23 October 2007

2007-10-23T01:39:51Z

Srmclare at 01:37, 23 October 2007

2007-10-23T01:37:11Z

Srmclare at 01:36, 23 October 2007

2007-10-23T01:36:20Z

Srmclare at 01:09, 23 October 2007

2007-10-23T01:09:45Z

Srmclare at 01:08, 23 October 2007

2007-10-23T01:08:56Z

@@ Line 172: / Line 172: @@
   abstract = {Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statistical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 249 degrees of freedom and generates a discrimination entropy of about 3.2 b/mm/sup 2/ over the iris, enabling real-time decisions about personal identity with extremely high confidence. The high confidence levels are important because they allow very large databases to be searched exhaustively (one-to-many "identification mode") without making false matches, despite so many chances. Biometrics that lack this property can only survive one-to-one ("verification") or few comparisons. The paper explains the iris recognition algorithms and presents results of 9.1 million comparisons among eye images from trials in Britain, the USA, Japan, and Korea. }
+  }
 </bibtex>
@@ Line 191: / Line 189: @@
+  }
 </bibtex>

@@ Line 212: / Line 212: @@
   author = {A. Simon, D. M. Worthen, and J. A. Mitas},
   title = {An evaluation of iridology},
-  journal = {Journal of Ameerican Medical Assoc},
+  journal = {Journal of American Medical Assoc},
   volume = {242},
   pages = {1385--1387},

@@ Line 209: / Line 209: @@
 <bibtex>
-@paper {simon001,
+@article{simon001,
   author = {A. Simon, D. M. Worthen, and J. A. Mitas},
   title = {An evaluation of iridology},

@@ Line 173: / Line 173: @@
+  }
-@article{328110,
- author = {Anil Jain and Lin Hong and Sharath Pankanti},
- title = {Biometric identification},
- journal = {Commun. ACM},
- volume = {43},
- number = {2},
- year = {2000},
- issn = {0001-0782},
- pages = {90--98},
- doi = {http://doi.acm.org/10.1145/328236.328110},
- publisher = {ACM Press},
- address = {New York, NY, USA},
-−
 </bibtex>

@@ Line 186: / Line 186: @@
   address = {New York, NY, USA},
+  }
+<bibtex>
 </bibtex>

@@ Line 168: / Line 168: @@
   pages = {21--30},
   doi = {http://dx.doi.org/10.1109/TCSVT.2003.818350},
   abstract = {Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statistical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 249 degrees of freedom and generates a discrimination entropy of about 3.2 b/mm/sup 2/ over the iris, enabling real-time decisions about personal identity with extremely high confidence. The high confidence levels are important because they allow very large databases to be searched exhaustively (one-to-many "identification mode") without making false matches, despite so many chances. Biometrics that lack this property can only survive one-to-one ("verification") or few comparisons. The paper explains the iris recognition algorithms and presents results of 9.1 million comparisons among eye images from trials in Britain, the USA, Japan, and Korea. }

← Older revision		Revision as of 01:36, 23 October 2007
Line 156:		Line 156:

	</bibtex>		</bibtex>
		+
		+	<bibtex>
		+	@article{doro01,
		+	author = {Daugman, J. },
		+	title = {How iris recognition works},
		+	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
		+	volume = {14},
		+	number = {1},
		+	month = {January},
		+	year = {2004},
		+	pages = {21--30},
		+	doi = {http://dx.doi.org/10.1109/TCSVT.2003.818350},
		+
		+	abstract = {Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statistical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 249 degrees of freedom and generates a discrimination entropy of about 3.2 b/mm/sup 2/ over the iris, enabling real-time decisions about personal identity with extremely high confidence. The high confidence levels are important because they allow very large databases to be searched exhaustively (one-to-many "identification mode") without making false matches, despite so many chances. Biometrics that lack this property can only survive one-to-one ("verification") or few comparisons. The paper explains the iris recognition algorithms and presents results of 9.1 million comparisons among eye images from trials in Britain, the USA, Japan, and Korea. }
		+	}
		+
		+	</bibtex>
		+

	=Surveys=		=Surveys=

@@ Line 175: / Line 175: @@
   author = {A. Simon, D. M. Worthen, and J. A. Mitas},
   title = {An evaluation of iridology},
-  pub = {Journal of Ameerican Medical Assoc},
+  journal = {Journal of Ameerican Medical Assoc},
   vol = {242},
   pages = { 1385--1387},