Secured Biometric Template Matching by Using Linear Discriminant Analysis

  • Surbhi Vijh
  • Deepak GaurEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 734)


Now a days 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.


Biometric template Logistic Mapped Encryption Algorithm Linear Discriminant Analysis (LDA) 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.ASET, Amity UniversityNoidaIndia
  2. 2.Department of Computer ScienceASET, Amity UniversityNoidaIndia

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