Contactless Biometric Fingerprint and Signature Identification and Verification

Authors

  • Dr. D. Thilagavathy  Professor, Department of IT, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
  • N. Deepasri  UG Student, Department of IT, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
  • P. Gahana  UG Student, Department of IT, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
  • S. Nivethasree  UG Student, Department of IT, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
  • M. Varshini  UG Student, Department of IT, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India

Keywords:

Service Oriented Architecture (SOA), State-of- the-Art, Support Vector Machine (SVM), Deep Neural Network (DNN), Knuckle Patterns.

Abstract

To query the biometric and fingerprint and signature identification, the database communicates with a single secure server as if the entire database is stored in it. In CSP, outsourced encrypted biometric and fingerprint and signature identification are stored in a distributed manner, whereas the secure server manages the query processing on such a distributed database. The desired data will be distributed and stored in secure servers which increases the verification of accessing data. It stores data in a particular cloud server from which the server distributes them based on availability and performance. It increases the security of the verification process by comparing the details stored. Study on signature and finger knuckle patterns has attracted increasing attention for the automated biometric signature identification. Signature and finger knuckle pattern is essentially a biometric identifier and the usage or availability of 2D knuckles and key limitations to avail biometric identifiers. So the proposal since proposes 2D signature and finger knuckle collection of data, which was gathered from various sources using a photometric imaging stereo approach. This paper investigates on 2D information from signature and finger knuckle patterns and introduces a new feature descriptor to extract discriminative features for accurate signature and finger knuckle matching. An individuality model for the proposed feature descriptor is also presented. Expected experimental analysis by consuming state of the art technology on the signature and finger pattern executes and validates the efficiency of the proposal. This process is verified from the obtained results, using the state of the art technique, signature and fingerprint collection patterns on available datasets that are distributed.

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International Journal of Scientific Research in Science and Technology

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Published

2020-03-05

Issue

Volume 5, Issue 5, March-April-2020

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. D. Thilagavathy, N. Deepasri, P. Gahana, S. Nivethasree, M. Varshini, " Contactless Biometric Fingerprint and Signature Identification and Verification, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 5, Issue 5, pp.189-197, March-April-2020.