文章基本信息

标题：ELM-Based Indonesia Vehicle License Plate Recognition System
本地全文：下载
作者：Basuki Rahmat ; Endra Joelianto ; I Ketut Eddy Purnama 等
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2021
卷号：328
页码：1-7
DOI：10.1051/e3sconf/202132802005
语种：English
出版社：EDP Sciences
摘要：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%.
关键词：Idiopathic Thrombocytopenic Purpura;Expert System;KNN;Certainty Factor