TY - JOUR
T1 - ELM-Based Indonesia Vehicle License Plate Recognition System
AU - Rahmat, Basuki
AU - Joelianto, Endra
AU - Purnama, I. Ketut Eddy
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© The Authors, published by EDP Sciences.
PY - 2021/12/6
Y1 - 2021/12/6
N2 - 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%.
AB - 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%.
KW - Certainty Factor
KW - Expert System
KW - Idiopathic Thrombocytopenic Purpura
KW - KNN
UR - http://www.scopus.com/inward/record.url?scp=85146983785&partnerID=8YFLogxK
U2 - 10.1051/e3sconf/202132802005
DO - 10.1051/e3sconf/202132802005
M3 - Conference article
AN - SCOPUS:85146983785
SN - 2267-1242
VL - 328
JO - E3S Web of Conferences
JF - E3S Web of Conferences
M1 - 02005
T2 - 2021 International Conference on Science and Technology, ICST 2021
Y2 - 27 October 2021 through 28 October 2021
ER -