Rancang Bangun Sistem Pengenalan Plat Nomor Kendaraan Menggunakan Jaringan Saraf Tiruan Backpropagation

Shabri Putra Wirman, Neneng Fitrya, Rahmat Junaidi, Noviarni Gafura Rizki
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引用次数: 0

Abstract

The manual parking system allows for errors in recording, the service takes a long time, and there is no history of vehicle users. The vehicle license plate recognition system is designed as an alternative parking system that is more accurate in recording, fast service, and the presence of vehicle user data. Vehicle license plate recognition system has been designed equipped with Backpropagation Artificial Neural Network (ANN). The recognition system that has been designed in advance goes through an image processing process with grayscale, black and white, segmentation, and principal component analysis (PCA) stages. The system is integrated with backpropagation ANN with multi layer network with the best results at layer1 550 and layer2 500. The number plate recognition system is equipped with a Graphycal User Interface (GUI) to display the identification results of vehicle number plate identification. The results of identification number plate recognition resulted in 100% training accuracy and 97.95918367% testing accuracy.
设计一个车牌识别系统,使用假的神经通量网络
手动停车系统允许记录错误,服务时间长,并且没有车辆用户的历史记录。车牌识别系统被设计为一种记录更准确、服务更快、车辆用户数据存在性更强的替代停车系统。设计了基于反向传播人工神经网络(ANN)的车牌识别系统。事先设计好的识别系统要经过灰度、黑白、分割、主成分分析(PCA)等阶段的图像处理过程。该系统与多层网络反向传播人工神经网络相结合,在1550层和25500层效果最好。车牌识别系统采用图形用户界面(GUI)显示车辆车牌识别结果。车牌识别的训练准确率为100%,测试准确率为97.95918367%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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