基于小波和欧氏距离特性提取的亚麻分类晚线

Vincentius Abdi Gunawan, Ignatia Imelda Fitriani, L. Putra
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引用次数: 1

摘要

驾驶是人类日常生活中经常进行的活动之一。驾驶可以通过陆地、空中和海上进行。人类驾驶的机动性在陆地道路上使用各种交通工具是非常高的。为了平稳行驶,道路上往往在每个交通区域设置交通标志。交通标志是道路使用者向驾驶人士提供有关周围情况的信息和指引的一种手段。缺乏阅读交通标志知识意识的驾车者的数量是印度尼西亚事故的最大原因之一。所以需要一个系统来帮助识别交通标志,尤其是禁止通行的标志。系统设计采用Haar小波特征提取和欧氏距离作为分类方法。从已经测试的数据来看,阅读交通标志的识别水平被禁止了92%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Klasifikasi Rambu Lalu Lintas Menggunakan Ekstraksi Ciri Wavelet Dan Jarak Euclidean
Driving is one of the human activities in which daily life is often done.  Driving can be done by land, air, and sea.  Human mobility in driving is very high on land routes using various means of transportation.  For the sake of smooth driving, roads are often equipped with traffic signs in each traffic area.  Traffic signs are a means for road users to provide information and guidance for motorists about the situation in the surrounding area.  The number of motorists who lack awareness of the knowledge of reading traffic signs is one of the biggest causes of accidents in Indonesia.  So that a system is needed that can help in recognizing traffic signs, especially prohibited signs.  The system designed using Haar Wavelet feature extraction and Euclidean distance as a classification.  From the data that has been tested, the level of recognition in reading traffic signs is prohibited by 92%.
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