Finger Vein Recognition Using Pattern Matching and Corner Detection Strategies
DOI:
https://doi.org/10.61841/z7dyec52Keywords:
Biometric Identification, Personal Authentication, Physical Features, Neural NetworkAbstract
Now-a-days, storing places are given some kind of protection for security purposes, like a password, pin number, or using any biometric identification system. For personal authentication, identification systems are used that utilize finger vein physiological biometric technology. This type of authentication is based on the finger vein pattern’s physical feature. In conventional techniques, a combination of genetic algorithms and selection based on correlation filters are used to generate a user-specific threshold in the branch tracking step. An improved fuzzy clustering algorithm is used for deciding the nearest points between samples. However, in the vein extraction stage, exact finding of the corner becomes a very difficult task. To solve this issue, a corner detection algorithm is utilized for feature extraction (corner points) from the images of finger veins, where pattern matching is based on the corner difference, which is represented in point form using a neural network classifier. Analysis is carried out on the database of Hong Kong Polytechnic University (HKPU) to demonstrate the robustness of the proposed technique with respect to accuracy, specificity, sensitivity, recall, and precision.
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