A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison
Abstract The recent developments of information technologies, and the consequent need for access to distributed services and resources, require robust and reliable authentication systems. Biometric systems can guarantee high levels of security and multimodal techniques, which combine two or more bio...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Hindawi-IET
2021-01-01
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| Series: | IET Biometrics |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/bme2.12001 |
| _version_ | 1797422829631700992 |
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| author | Vincenzo Conti Leonardo Rundo Carmelo Militello Valerio Mario Salerno Salvatore Vitabile Sabato Marco Siniscalchi |
| author_facet | Vincenzo Conti Leonardo Rundo Carmelo Militello Valerio Mario Salerno Salvatore Vitabile Sabato Marco Siniscalchi |
| author_sort | Vincenzo Conti |
| collection | DOAJ |
| description | Abstract The recent developments of information technologies, and the consequent need for access to distributed services and resources, require robust and reliable authentication systems. Biometric systems can guarantee high levels of security and multimodal techniques, which combine two or more biometric traits, warranting constraints that are more stringent during the access phases. This work proposes a novel multimodal biometric system based on iris and retina combination in the spatial domain. The proposed solution follows the alignment and recognition approach commonly adopted in computational linguistics and bioinformatics; in particular, features are extracted separately for iris and retina, and the fusion is obtained relying upon the comparison score via the Levenshtein distance. We evaluated our approach by testing several combinations of publicly available biometric databases, namely one for retina images and three for iris images. To provide comprehensive results, detection error trade‐off‐based metrics, as well as statistical analyses for assessing the authentication performance, were considered. The best achieved False Acceptation Rate and False Rejection Rate indices were and 3.33%, respectively, for the multimodal retina‐iris biometric approach that overall outperformed the unimodal systems. These results draw the potential of the proposed approach as a multimodal authentication framework using multiple static biometric traits. |
| first_indexed | 2024-03-09T07:39:02Z |
| format | Article |
| id | doaj.art-289cd4859316431caa8c13c1317b07cc |
| institution | Directory Open Access Journal |
| issn | 2047-4938 2047-4946 |
| language | English |
| last_indexed | 2024-03-09T07:39:02Z |
| publishDate | 2021-01-01 |
| publisher | Hindawi-IET |
| record_format | Article |
| series | IET Biometrics |
| spelling | doaj.art-289cd4859316431caa8c13c1317b07cc2023-12-03T05:16:41ZengHindawi-IETIET Biometrics2047-49382047-49462021-01-01101446410.1049/bme2.12001A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparisonVincenzo Conti0Leonardo Rundo1Carmelo Militello2Valerio Mario Salerno3Salvatore Vitabile4Sabato Marco Siniscalchi5Faculty of Engineering and Architecture University of Enna KORE Enna ItalyDepartment of Radiology University of Cambridge Cambridge UKInstitute of Molecular Bioimaging and Physiology Italian National Research Council (IBFM‐CNR) Cefalù ItalyFaculty of Engineering and Architecture University of Enna KORE Enna ItalyDepartment of Biomedicine Neuroscience and Advanced Diagnostics (BiND) University of Palermo Palermo ItalyFaculty of Engineering and Architecture University of Enna KORE Enna ItalyAbstract The recent developments of information technologies, and the consequent need for access to distributed services and resources, require robust and reliable authentication systems. Biometric systems can guarantee high levels of security and multimodal techniques, which combine two or more biometric traits, warranting constraints that are more stringent during the access phases. This work proposes a novel multimodal biometric system based on iris and retina combination in the spatial domain. The proposed solution follows the alignment and recognition approach commonly adopted in computational linguistics and bioinformatics; in particular, features are extracted separately for iris and retina, and the fusion is obtained relying upon the comparison score via the Levenshtein distance. We evaluated our approach by testing several combinations of publicly available biometric databases, namely one for retina images and three for iris images. To provide comprehensive results, detection error trade‐off‐based metrics, as well as statistical analyses for assessing the authentication performance, were considered. The best achieved False Acceptation Rate and False Rejection Rate indices were and 3.33%, respectively, for the multimodal retina‐iris biometric approach that overall outperformed the unimodal systems. These results draw the potential of the proposed approach as a multimodal authentication framework using multiple static biometric traits.https://doi.org/10.1049/bme2.12001biometrics (access control)computational linguisticseyefeature extractionimage recognitioniris recognition |
| spellingShingle | Vincenzo Conti Leonardo Rundo Carmelo Militello Valerio Mario Salerno Salvatore Vitabile Sabato Marco Siniscalchi A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison IET Biometrics biometrics (access control) computational linguistics eye feature extraction image recognition iris recognition |
| title | A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison |
| title_full | A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison |
| title_fullStr | A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison |
| title_full_unstemmed | A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison |
| title_short | A multimodal retina‐iris biometric system using the Levenshtein distance for spatial feature comparison |
| title_sort | multimodal retina iris biometric system using the levenshtein distance for spatial feature comparison |
| topic | biometrics (access control) computational linguistics eye feature extraction image recognition iris recognition |
| url | https://doi.org/10.1049/bme2.12001 |
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