Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks

Abdul Rafay; Yumnah Hasan; Adnan Iqbal

doi:10.1007/978-3-030-03405-4_26

Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks

Abdul Rafay
, Yumnah Hasan
, Adnan Iqbal

Bahria University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2
Editors	Rahul Bhatia, Supriya Kapoor, Kohei Arai
Publisher	Springer Verlag
Pages	385-397
Number of pages	13
ISBN (Print)	9783030034047
DOIs	https://doi.org/10.1007/978-3-030-03405-4_26
Publication status	Published - 2019
Externally published	Yes
Event	Future of Information and Communication Conference, FICC 2018 - Singapore, Singapore Duration: 5 Apr 2018 → 6 Apr 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	887
ISSN (Print)	2194-5357

Conference

Conference	Future of Information and Communication Conference, FICC 2018
Country/Territory	Singapore
City	Singapore
Period	5/04/18 → 6/04/18

Keywords

Artificial neural networks
Biometric processor
Multilayer feed forward network
Pattern recognition

Access to Document

10.1007/978-3-030-03405-4_26

Cite this

Rafay, A., Hasan, Y., & Iqbal, A. (2019). Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks. In R. Bhatia, S. Kapoor, & K. Arai (Eds.), Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2 (pp. 385-397). (Advances in Intelligent Systems and Computing; Vol. 887). Springer Verlag. https://doi.org/10.1007/978-3-030-03405-4_26

Rafay, Abdul ; Hasan, Yumnah ; Iqbal, Adnan. / Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks. Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2. editor / Rahul Bhatia ; Supriya Kapoor ; Kohei Arai. Springer Verlag, 2019. pp. 385-397 (Advances in Intelligent Systems and Computing).

@inproceedings{3300752b28624c8d86449bf241082a4c,

title = "Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks",

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",

author = "Abdul Rafay and Yumnah Hasan and Adnan Iqbal",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; Future of Information and Communication Conference, FICC 2018 ; Conference date: 05-04-2018 Through 06-04-2018",

year = "2019",

doi = "10.1007/978-3-030-03405-4\_26",

language = "English",

isbn = "9783030034047",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "385--397",

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}

Rafay, A, Hasan, Y & Iqbal, A 2019, Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks. in R Bhatia, S Kapoor & K Arai (eds), Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2. Advances in Intelligent Systems and Computing, vol. 887, Springer Verlag, pp. 385-397, Future of Information and Communication Conference, FICC 2018, Singapore, Singapore, 5/04/18. https://doi.org/10.1007/978-3-030-03405-4_26

Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks. / Rafay, Abdul; Hasan, Yumnah; Iqbal, Adnan.
Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2. ed. / Rahul Bhatia; Supriya Kapoor; Kohei Arai. Springer Verlag, 2019. p. 385-397 (Advances in Intelligent Systems and Computing; Vol. 887).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks

AU - Rafay, Abdul

AU - Hasan, Yumnah

AU - Iqbal, Adnan

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Artificial neural networks

KW - Biometric processor

KW - Multilayer feed forward network

KW - Pattern recognition

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U2 - 10.1007/978-3-030-03405-4_26

DO - 10.1007/978-3-030-03405-4_26

M3 - Conference contribution

AN - SCOPUS:85059326719

SN - 9783030034047

T3 - Advances in Intelligent Systems and Computing

SP - 385

EP - 397

BT - Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2

A2 - Bhatia, Rahul

A2 - Kapoor, Supriya

A2 - Arai, Kohei

PB - Springer Verlag

T2 - Future of Information and Communication Conference, FICC 2018

Y2 - 5 April 2018 through 6 April 2018

ER -

Rafay A, Hasan Y, Iqbal A. Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks. In Bhatia R, Kapoor S, Arai K, editors, Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 2. Springer Verlag. 2019. p. 385-397. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-03405-4_26

Recognition of fingerprint biometric system access control for car memory settings through artificial neural networks

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