Secured Biometric Template matching by using Linear Discriminant Analysis

Authors

  • Surbhi vij
  • Deepak Gaur

Keywords:

Biometric Template, Logistic Mapped Encryption Algorithm, Security, Fingerprint, Linear Discriminant analysis (LDA)

Abstract

Now a day’s biometric template matching is of great concern in forensic science. There are different technical classifiers to find out the matching between these templates such as Naïve Bayes classifiers, PCA algorithm, SVM classifier etc. Different classifier gave the different level of accuracy results. All of above these classifiers, Linear Discriminant analysis (LDA) is the classifier which always give best direction of projection for number of classes of features. So, in our experimental result, we use the Linear Discriminant analysis (LDA) to find out the matching between biometric templates. We took the data set of fingerprints; make these fingerprints secured by using Logistic Mapped encryption algorithm. Apply the pre-possessing and post-processing on these encoded fingerprints and matched the fingerprints to the data set by using LDA. Simulated model was found to measure the accurate percentage results of biometric templates.

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Published

2017-07-01

How to Cite

Surbhi vij, & Deepak Gaur. (2017). Secured Biometric Template matching by using Linear Discriminant Analysis. Journal of Network and Innovative Computing, 5, 8. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/136

Issue

Vol. 5 (2017)

Section

Original Article

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