基于HAAR级联分类器的交通信号灯自动识别救护车

Eldha Nur Ramadhana Putra, Edi Prihartono, Budi Santoso
{"title":"基于HAAR级联分类器的交通信号灯自动识别救护车","authors":"Eldha Nur Ramadhana Putra, Edi Prihartono, Budi Santoso","doi":"10.25139/ijair.v2i2.3194","DOIUrl":null,"url":null,"abstract":"Lack of knowledge by road users regarding these priorities, especially when there is a passing ambulance that is often stuck in traffic at a crossroads due to accumulated vehicles and the traffic light is still red. The purpose of this paper is to simulate traffic light automation by giving a green light every time an ambulance passes by using the HAAR and Computer Vision methods. The HAAR method is used for training data from less sharp images as part of the Ambulance object classification process. The Computer Vision method is used as a tool in image processing objects to processing the image captured by the Camera. Hardware through the microphone performs pattern recognition to pick up ambulance sirens. The test result at the average frequency caught by the microphone is 1.3 kHz. The test results of the System to capture ambulance objects received a precision value of 75%, a recall of 100%, and an accuracy of 75%.","PeriodicalId":365842,"journal":{"name":"International Journal of Artificial Intelligence & Robotics (IJAIR)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Traffic Light Automation with Camera Tracker and Microphone to Recognize Ambulance Using the HAAR Cascade Classifier Method\",\"authors\":\"Eldha Nur Ramadhana Putra, Edi Prihartono, Budi Santoso\",\"doi\":\"10.25139/ijair.v2i2.3194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lack of knowledge by road users regarding these priorities, especially when there is a passing ambulance that is often stuck in traffic at a crossroads due to accumulated vehicles and the traffic light is still red. The purpose of this paper is to simulate traffic light automation by giving a green light every time an ambulance passes by using the HAAR and Computer Vision methods. The HAAR method is used for training data from less sharp images as part of the Ambulance object classification process. The Computer Vision method is used as a tool in image processing objects to processing the image captured by the Camera. Hardware through the microphone performs pattern recognition to pick up ambulance sirens. The test result at the average frequency caught by the microphone is 1.3 kHz. The test results of the System to capture ambulance objects received a precision value of 75%, a recall of 100%, and an accuracy of 75%.\",\"PeriodicalId\":365842,\"journal\":{\"name\":\"International Journal of Artificial Intelligence & Robotics (IJAIR)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Artificial Intelligence & Robotics (IJAIR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25139/ijair.v2i2.3194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence & Robotics (IJAIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25139/ijair.v2i2.3194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

道路使用者对这些优先事项缺乏了解,特别是当一辆救护车经过时,由于车辆积聚而经常在十字路口受阻,而交通灯仍然是红色的。本文的目的是利用HAAR和计算机视觉方法模拟交通信号灯自动化,每次救护车通过时都给绿灯。HAAR方法用于从较不清晰的图像中训练数据,作为救护车对象分类过程的一部分。计算机视觉方法作为图像处理对象的工具,对摄像机捕获的图像进行处理。硬件通过麦克风执行模式识别来接收救护车的警报声。在麦克风捕获的平均频率下的测试结果为1.3 kHz。系统捕获救护车对象的测试结果精度值为75%,召回率为100%,准确率为75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Traffic Light Automation with Camera Tracker and Microphone to Recognize Ambulance Using the HAAR Cascade Classifier Method
Lack of knowledge by road users regarding these priorities, especially when there is a passing ambulance that is often stuck in traffic at a crossroads due to accumulated vehicles and the traffic light is still red. The purpose of this paper is to simulate traffic light automation by giving a green light every time an ambulance passes by using the HAAR and Computer Vision methods. The HAAR method is used for training data from less sharp images as part of the Ambulance object classification process. The Computer Vision method is used as a tool in image processing objects to processing the image captured by the Camera. Hardware through the microphone performs pattern recognition to pick up ambulance sirens. The test result at the average frequency caught by the microphone is 1.3 kHz. The test results of the System to capture ambulance objects received a precision value of 75%, a recall of 100%, and an accuracy of 75%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Emotion Detection in Twitter Social Media Using Long Short-Term Memory (LSTM) and Fast Text Traffic Light Automation with Camera Tracker and Microphone to Recognize Ambulance Using the HAAR Cascade Classifier Method Message Security Using Rivest-Shamir-Adleman Cryptography and Least Significant Bit Steganography with Video Platform An Automatic Sliding Doors Using RFID and Arduino An Implementation of MMS Steganography With The LSB Method
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1