Abstract
SIFT-based identification techniques have been broadly criticised in biometrics due to its high false matching rate. To overcome this weakness, a new method for SIFT-based palmprint matching, called the Self Geometric Relationship-based matching (SGR-Matching) is presented. While existing matching techniques consider only the relationship between the SIFT-points of the query image on one hand and the points in the reference image on the other hand, SGR-Matching also takes into account the geometric relationship between the SIFT-points within the query image in comparison with the relationship of the corresponding matched points in the reference image. Assessed with the proposed SGR-Matching, the SIFT-based palmprint identification system has been shown to improve the performance significantly. Furthermore, experimental results have shown the superiority of the proposed technique over state-of-the-art techniques.
Original language | English |
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DOIs | |
Publication status | Published - 29 May 2017 |
Event | IWBF 2017 - 5th International Workshop on Biometrics and Forensics - Coventry, UK Duration: 29 May 2017 → … |
Workshop
Workshop | IWBF 2017 - 5th International Workshop on Biometrics and Forensics |
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Period | 29/05/17 → … |
Keywords
- Feature extraction
- Histograms
- Biometrics (access control)
- Encoding
- Databases
- Computers
- Electronic mail