[1]时佳琦,李 威.黑烟车检测方法综述[J].计算机技术与发展,2022,32(S2):16-24.[doi:10. 3969 / j. issn. 1673-629X. 2022. S2. 003]
　SHI Jia-qi,LI Wei.Survey on Smoky Vehicle Detection[J].,2022,32(S2):16-24.[doi:10. 3969 / j. issn. 1673-629X. 2022. S2. 003]
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黑烟车检测方法综述()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年S2期
页码:
16-24
栏目:
综述
出版日期:
2022-12-11

文章信息/Info

Title:
Survey on Smoky Vehicle Detection
文章编号:
1673-629X(2022)S2-0016-09
作者:
时佳琦; 李 威
沈阳工业大学 信息科学与工程学院,辽宁 沈阳 110870
Author(s):
SHI Jia-qi; LI Wei
School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,China
关键词:
黑烟车检测; 目标检测; 特征提取; 黑烟检测; 运动车辆检测
Keywords:
smoky vehicle detection; target detection; feature extraction; smoky detection; moving vehicle detection
分类号:
TP391. 4
DOI:
10. 3969 / j. issn. 1673-629X. 2022. S2. 003
摘要:
黑烟车检测具有响应速度快、不易受环境因素影响、人工成本低等优势,为交警执法提供了依据,能够更有效地从源头治理尾气排放不达标的车辆。 近年逐渐出现黑烟车检测方法,这些方法尽管能够实现黑烟车检测功能,但大部分公开发表的文献并未公布检测效果。 为展现黑烟车检测的进展,重点针对 2016 年至 2021 年国内外公开发表的主要文献,进行全面的梳理和分析。 在黑烟车检测的基本框架上,重点围绕运动车辆目标检测、大型车辆尾部排烟区域定位和黑烟检测这三方面进行分析和总结,对传统方法和深度学习方法进行归纳。 重点针对基于传统前景检测的车辆检测方法和基于深度学习的车辆检测方法进行梳理;梳理大型车辆排烟区定位的方法;梳理车辆尾部排烟区 ROI 的静态特征和动态特征及针对提取的特征所使用的分类器。 通过对已发表的文献梳理,总结近几年黑烟车检测取得的进展和存在的不足,对发展前景进行展望。 针对黑烟车检测的研究近年来逐渐受到重视,各种各样的检测思路逐渐涌现。 通过对已有文献进行全面梳理和分析,期望黑烟车检测能够取得更大的进展并更好地应用于工业领域,为检查违规车辆提供更有力的技术支撑。
Abstract:
Smoky vehicle detection has the advantage of quick response,not liable to be affected by external condition and low labor cost.It provides a basis for traffic police to enforce the law,can more efficiently control the vehicles whose emission is not up to the standardfrom the source. In recent years,the methods of smoky vehicle detection have gradually emerged. Although these methods can achievethe function of smoky vehicle detection,the effects have not been published in most of the published papers. In order to show the progressof smoky vehicle detection,the main literature published at home and abroad since 2016 to 2021 has been comprehensively sorted out andanalyzed. Based on the basic framework of smoky vehicle detection,focus on the analysis and summary of vehicle detection,vehicle tailfeature extraction and classification,and license plate recognition,summarize the traditional methods and deep learning methods. Focus onvehicle detection methods based on traditional foreground detection and vehicle detection methods based on deep learning; sort out thestatic and dynamic features of the ROI at the rear of the vehicle and the classifier used for the extracted features; arrange the license platerecognition methods based on traditional methods and deep learning methods. By combing the published literature, summarize theprogress and shortcomings of black smoke vehicle detection in recent years, and look forward to the development prospect. In recentyears,more and more attention has been paid to the detection of smoky vehicles. Through a comprehensive review and analysis of theexisting literature,it is expected that smoke vehicle detection can make greater progress and be better applied in the industrial field,providing more powerful technical support for the inspection of illegal vehicles.

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更新日期/Last Update: 2022-10-10