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Recognition of Fingerprint Biometric System Access Control for Car Memory Settings Through Artificial Neural Networks

  • Abdul RafayEmail author
  • Yumnah Hasan
  • Adnan Iqbal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 887)

Abstract

Recognition and authentication are important factors for implementation in every computerized system. This particularly plays a significant role in electronic banking and luxurious cars. PIN code or key can be lost or stolen by an imposter. Therefore, the characteristics of humans are the best recognition points to authenticate a user. Artificial Neural Network (ANN) is the only computational network which works as the working of human brain and its neurons function by adopting the features of a human. In this research, we have proposed an algorithm for training of fingerprint biometric system by implementing Artificial Neural Networks for the recognition of finger features of the human. The method includes detection of minutiae values of the ridge termination and bifurcation points. The multilayer feed forward network is the successful network with error back propagation algorithm for pattern recognition through supervised learning. This network is being used in many applications of recognition and control. This architecture is applicable for finger minutiae extraction for recognition of car user and its features through memory settings. This network gives 99% correct classification for recognition of the user.

Keywords

Artificial Neural Networks Biometric processor Multilayer feed forward network Pattern recognition 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Electrical Engineering DepartmentBahria UniversityKarachiPakistan

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