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| Content Provider | IET Digital Library |
|---|---|
| Author | Lakshmanan, Latha |
| Abstract | A two-stage geometric approach that is both scale and rotation invariant is implemented for extracting the unique features present in the surface of an ear image. As occlusion because of ear rings and hair significantly affect the efficiency of ear recognition process, only the middle portion of the ear is considered in this work. The resultant matching scores are compared against a threshold to make a decision for authenticating a person. It is found that the fused scores obtained from the two levels of feature extraction enhance the recognition accuracy compared with that of the individual stages. Finally, particle swarm optimisation technique is applied on the matching scores in order to optimise the fusion parameters such as decision threshold and weights. It results in further improved verification rates compared with the fusion of scores without optimisation. Thus, the proposed method works on partial ear images and demonstrate the presence of more unique features in the middle part of the ear (as seen by the increase in recognition accuracy) and the method also aids in reducing the computation time. |
| Starting Page | 97 |
| Ending Page | 106 |
| Page Count | 10 |
| ISSN | 20474938 |
| Volume Number | 2 |
| e-ISSN | 20474946 |
| Issue Number | Issue 3, Sep (2013) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-bmt/2/3 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2012.0049 |
| Journal | IET Biometrics |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Computer Vision And Image Processing Technique Ear Ear Image Ear Recognition Process Ear Rings Ear Scores Efficient Person Authentication Feature Extraction Image Recognition Multilevel Fusion Rotation Invariant Scale Invariant Two Stage Geometric Approach |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Computer Vision and Pattern Recognition Software |
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