An implementation of Gabor based adaptive matching pursuit for multi-modal biometric registration
| dc.contributor.advisor | Hudson, Fred | |
| dc.contributor.author | Bartlett, Jonathan D. | |
| dc.contributor.committeeMember | Agaian, Sos | |
| dc.contributor.committeeMember | Akopian, David | |
| dc.date.accessioned | 2024-01-25T22:34:12Z | |
| dc.date.available | 2024-01-25T22:34:12Z | |
| dc.date.issued | 2010 | |
| dc.description | This item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID. | |
| dc.description.abstract | This research describes the design and implementation of a novel Gabor-based Adaptive Matching Pursuit Algorithm applied to voice data for Multi-modal Biometrics Registration. Combining the resultant voice feature hyperspace vector with the average absolute deviation feature vector created by [Rosa2005], we are able to fuse the two data types together at the feature level into a 940 dimensional multi-modal biometrics feature vector. Our multi-modal biometrics feature extraction system attempts to alleviate some of the weaknesses of single mode systems by introducing multiple modes of sensor data which when combined, make for a more robust system that is less prone to spoofing, mechanical failure and error caused by noise in single mode biometrics. | |
| dc.description.department | Electrical and Computer Engineering | |
| dc.format.extent | 85 pages | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.isbn | 9781124385013 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12588/2481 | |
| dc.language | en | |
| dc.subject | Biometrics | |
| dc.subject | Fingerprint | |
| dc.subject | Gabor | |
| dc.subject | Matching Pursuit | |
| dc.subject | Multimodal | |
| dc.subject | Voice | |
| dc.subject.classification | Electrical engineering | |
| dc.title | An implementation of Gabor based adaptive matching pursuit for multi-modal biometric registration | |
| dc.type | Thesis | |
| dc.type.dcmi | Text | |
| dcterms.accessRights | pq_closed | |
| thesis.degree.department | Electrical and Computer Engineering | |
| thesis.degree.grantor | University of Texas at San Antonio | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science |
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