| Issue |
E3S Web Conf.
Volume 328, 2021
International Conference on Science and Technology (ICST 2021)
|
|
|---|---|---|
| Article Number | 02005 | |
| Number of page(s) | 7 | |
| Section | Electrical, Intrumentation and control, Dynamic Electricity | |
| DOI | https://doi.org/10.1051/e3sconf/202132802005 | |
| Published online | 06 December 2021 | |
ELM-Based Indonesia Vehicle License Plate Recognition System
1 Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya, Indonesia
2 Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung 40132, Indonesia
3 Department of Electrical Engineering, Faculty of Industrial Technology, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
* Corresponding author : basukirahmat.if@upnjatim.ac.id
In this paper, a widely developed learning machine algorithm called Extreme Learning Machine (ELM) is used to recognize Indonesia vehicle license plates. The algorithm includes grayscale, binary, erosion, dilation and convolution processes, as well as the process of smearing, location determination and character segmentation before the ELM algorithm is applied. The algorithm includes one crucial and rarely performed technique for extraction of vehicle license plates, namely Smearing Algorithms. In the experimental results, ELM is compared with the template matching method. The obtained outcome of the average accuracy of both methods has the same value of 70.3175%.
Key words: Idiopathic Thrombocytopenic Purpura / Expert System / KNN / Certainty Factor
© The Authors, published by EDP Sciences, 2021
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