Issue |
E3S Web Conf.
Volume 130, 2019
The 1st International Conference on Automotive, Manufacturing, and Mechanical Engineering (IC-AMME 2018)
|
|
---|---|---|
Article Number | 01022 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/e3sconf/201913001022 | |
Published online | 15 November 2019 |
Automotive Start–Stop Engine Based on Fingerprint Recognition System
1
Automotive and Robotics Program, Computer Engineering Department, BINUS ASO School of Engineering, Bina Nusantara University,
Jakarta,
11480,
Indonesia
2
Computer Engineering Department, BINUS ASO School of Engineering, Bina Nusantara University,
Jl. K. H. Syahdan No. 9, Kemanggisan, Palmerah,
Jakarta,
11480
Indonesia
3
Faculty of Engineering, Technology and Built Environment, UCSI University,
Cheras,
Kuala Lumpur 56000
Malaysia
* Corresponding author:b wastuti@binus.edu
Automated vehicle security system plays an important rule in nowadays advance automotive technology. One of the methods which can be applied for a security system is based on biometric identification system. Fingerprint recognition is one of the biometric systems that can be applied to the security system. In this work, fingerprint recognition system to start the motorcycle engine is developed. The fingerprint of the owner and other authorized persons will be stored into the database, then while the time of starting the engine of the vehicle, the fingerprint will be validated with the database. The minutiae extraction method is applied to find the difference of fingerprint each other after turn the image into grayscale and thinning. After the extraction, the next step is finding the ridge edge and bifurcation. The result of the image will be used as input to the Artificial Neural Network (ANN) to recognize authorized person only. The experiment of fingerprint recognition system shows that automatic start-stop engine using fingerprint recognition system based minutiae extraction and Artificial Neural Network (ANN) has accuracy 100 % and 100 %, respectively.
Key words: Biometric recognition system / image processing / neural network
© The Authors, published by EDP Sciences, 2019
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