Improved Fuzzy Clustering (I FC ) and Correlation Based user Threshold Selection with TRI Branch for Finger Vein Recognition
K. Santhosh Kumar1, D. Maheswari2
1K. Santhosh Kumar, Muthayammal College of Engineering, Rasipuram (Tamil Nadu), India.
2D. Maheswari, Muthayammal College of Engineering, Rasipuram (Tamil Nadu), India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7519-7525 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5331118419/2019©BEIESP | DOI: 10.35940/ijrte.D5331.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: During the process of template matching with regard to finger vein identification, the probe used will get permitted only when the count of its vein points overlapping with the registered client is higher compared to the predetermined threshold. But, the admittance might be incorrect due to the neglect of the structure of the vein pattern. In the earlier works, the extraction of the vein structure (tri-branch) is done out of the vein pattern, and then combined with the entire vein pattern using a user-oriented threshold dependent filter setup. It renders a greater value of false acceptances, due to the User-oriented Threshold obtained from filter. In the step of branch tracking, the closest points are falsely detected, and therefore few tracking algorithms are needed. In order to resolve this, user-specific Threshold is generated on the basis of the correlation filter based selection combined with genetic algorithm. In the step of branch tracking, the closest points between the samples are decided by using the improved fuzzy clustering algorithm. It is observed that the local branches of the vein close to the segregation point of the vein pattern differ hugely from the fake pictures. The results of experiment carried out on two publicly available databases show the efficiency obtained of the novel design for boosting the performance achieved with respect to vein pattern based finger vein identification.
Keywords: Branch Tracking, Finger Vein, Genetic Algorithm, Improved Fuzzy Clustering Algorithm, Predefined Threshold, Tri-Branch Vein Structure, User-Specific Threshold And Vein Pattern.
Scope of the Article: Pattern Recognition.