Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person
Abstract When only one sample per person (OSPP) is registered in the gallery, it is difficult for ear recognition methods to sufficiently and effectively reduce the search range of the matching features, thus resulting in low computational efficiency and mismatch problems. A 3D ear biometric system...
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| Format: | Article |
| Language: | English |
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Wiley
2022-05-01
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| Series: | IET Biometrics |
| Online Access: | https://doi.org/10.1049/bme2.12067 |
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| _version_ | 1832559680219512832 |
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| author | Qinping Zhu Zhichun Mu Li Yuan |
| author_facet | Qinping Zhu Zhichun Mu Li Yuan |
| author_sort | Qinping Zhu |
| collection | DOAJ |
| description | Abstract When only one sample per person (OSPP) is registered in the gallery, it is difficult for ear recognition methods to sufficiently and effectively reduce the search range of the matching features, thus resulting in low computational efficiency and mismatch problems. A 3D ear biometric system using OSPP is proposed to solve this problem. By categorising ear images by shape and establishing the corresponding relationship between keypoints from ear images and regions (regional cluster) on the directional proposals that can be arranged to roughly face the ear image, the corresponding keypoints are obtained. Then, ear recognition is performed by combining corresponding keypoints and a multi‐keypoint descriptor sparse representation classification method. The experimental results conducted on the University of Notre Dame Collection J2 dataset yielded a rank‐1 recognition rate of 98.84%; furthermore, the time for one identification operation shared by each gallery subject was 0.047 ms. |
| format | Article |
| id | doaj-art-2b3c48f315044038b90539cd8bc9c7a5 |
| institution | Kabale University |
| issn | 2047-4938 2047-4946 |
| language | English |
| publishDate | 2022-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Biometrics |
| spelling | doaj-art-2b3c48f315044038b90539cd8bc9c7a52025-02-03T01:29:24ZengWileyIET Biometrics2047-49382047-49462022-05-0111322524810.1049/bme2.12067Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per personQinping Zhu0Zhichun Mu1Li Yuan2School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing ChinaSchool of Automation and Electrical Engineering University of Science and Technology Beijing Beijing ChinaSchool of Automation and Electrical Engineering University of Science and Technology Beijing Beijing ChinaAbstract When only one sample per person (OSPP) is registered in the gallery, it is difficult for ear recognition methods to sufficiently and effectively reduce the search range of the matching features, thus resulting in low computational efficiency and mismatch problems. A 3D ear biometric system using OSPP is proposed to solve this problem. By categorising ear images by shape and establishing the corresponding relationship between keypoints from ear images and regions (regional cluster) on the directional proposals that can be arranged to roughly face the ear image, the corresponding keypoints are obtained. Then, ear recognition is performed by combining corresponding keypoints and a multi‐keypoint descriptor sparse representation classification method. The experimental results conducted on the University of Notre Dame Collection J2 dataset yielded a rank‐1 recognition rate of 98.84%; furthermore, the time for one identification operation shared by each gallery subject was 0.047 ms.https://doi.org/10.1049/bme2.12067 |
| spellingShingle | Qinping Zhu Zhichun Mu Li Yuan Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person IET Biometrics |
| title | Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person |
| title_full | Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person |
| title_fullStr | Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person |
| title_full_unstemmed | Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person |
| title_short | Corresponding keypoint constrained sparse representation three‐dimensional ear recognition via one sample per person |
| title_sort | corresponding keypoint constrained sparse representation three dimensional ear recognition via one sample per person |
| url | https://doi.org/10.1049/bme2.12067 |
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