Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images
This paper develops an approach to measure the information content in a biometric feature representation of iris images. In this context, the biometric feature information is calculated using the relative entropy between the intraclass and interclass feature distributions. The collected data is regu...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2012/282589 |
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| _version_ | 1832560188338470912 |
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| author | R. Youmaran A. Adler |
| author_facet | R. Youmaran A. Adler |
| author_sort | R. Youmaran |
| collection | DOAJ |
| description | This paper develops an approach to measure the information content in a biometric feature representation of iris images. In this context, the biometric feature information is calculated using the relative entropy between the intraclass and interclass feature distributions. The collected data is regularized using a Gaussian model of the feature covariances in order to practically measure the biometric information with limited data samples. An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA-) and Independent-Component Analysis- (ICA-) based feature decomposition schemes. From this, the biometric feature information is calculated to be approximately 278 bits for PCA and 288 bits for ICA iris features using Masek's iris recognition scheme. This value approximately matches previous estimates of iris information content. |
| format | Article |
| id | doaj-art-7ae6174e53a646299258c7604013621c |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-7ae6174e53a646299258c7604013621c2025-02-03T01:28:14ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552012-01-01201210.1155/2012/282589282589Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris ImagesR. Youmaran0A. Adler1Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, K1S 5B6, CanadaDepartment of Systems and Computer Engineering, Carleton University, Ottawa, ON, K1S 5B6, CanadaThis paper develops an approach to measure the information content in a biometric feature representation of iris images. In this context, the biometric feature information is calculated using the relative entropy between the intraclass and interclass feature distributions. The collected data is regularized using a Gaussian model of the feature covariances in order to practically measure the biometric information with limited data samples. An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA-) and Independent-Component Analysis- (ICA-) based feature decomposition schemes. From this, the biometric feature information is calculated to be approximately 278 bits for PCA and 288 bits for ICA iris features using Masek's iris recognition scheme. This value approximately matches previous estimates of iris information content.http://dx.doi.org/10.1155/2012/282589 |
| spellingShingle | R. Youmaran A. Adler Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images Journal of Electrical and Computer Engineering |
| title | Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images |
| title_full | Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images |
| title_fullStr | Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images |
| title_full_unstemmed | Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images |
| title_short | Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images |
| title_sort | measuring biometric sample quality in terms of biometric feature information in iris images |
| url | http://dx.doi.org/10.1155/2012/282589 |
| work_keys_str_mv | AT ryoumaran measuringbiometricsamplequalityintermsofbiometricfeatureinformationinirisimages AT aadler measuringbiometricsamplequalityintermsofbiometricfeatureinformationinirisimages |