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首页> 外文会议>International Academic Conference on Frontiers in Social Sciences and Management Innovation >The Researches Detection Method of Illegal Parking Based on Convolutional Neural Network
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The Researches Detection Method of Illegal Parking Based on Convolutional Neural Network

机译：基于卷积神经网络的非法停车检测方法研究

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摘要

Violation of parking is a legal term. Our country's law stipulates that there should be no-stop signs and markings, road sections with isolation facilities between motor vehicles and non-motor vehicle lanes and sidewalks, and crosswalks and construction sites. No parking; Railway crossings, sharp bends, narrow roads with widths less than 4 meters, bridges, steep slopes, tunnels, and sections within 50 meters of the above locations are not allowed to stop. In recent years, urban management is gradually developing towards information There are corresponding treatment mechanisms for illegal parking in urban management, but the method of detecting illegal parking based on machine vision is still under study. This paper takes a street in Hebei Province as the research object, and studies the illegal parking under the surveillance image. It also proposes to use the machine vision-based method to automatically detect the illegal parking. In the monitoring image, according to the street view image information detected by the computer, A status assessment of the vehicle placement can be achieved. The detection algorithm in this paper uses the multi-angle suggestion area to accurately locate the offending vehicles in the image and mark them on the detected vehicles. The experimental data shows that the algorithm has good adaptability to the detection of illegal parking in surveillance images, and effectively improves the inspection efficiency.
机译：违反停车是一个法律术语。我国的法律规定，在机动车和非机动车通道和人行道和人行道和人行道和人行道之间的隔离设施，以及人行横道和人行道和施工场所之间应该有没有停止标志和标记，路段。禁止停车;铁路交叉口，尖锐的弯曲，宽度小于4米的狭窄道路，桥梁，陡坡，隧道和上述50米范围内的部分不允许停止。近年来，城市管理层逐步向信息发展逐步发展，对城市管理中的非法停车有相应的处理机制，但仍在研究基于机器视觉的非法停车的方法。本文占据了河北省的街道作为研究对象，并研究了监视图像下的非法停车。它还建议使用基于机器视觉的方法来自动检测非法停车位。在监视图像中，根据计算机检测到的街景图像信息，可以实现车辆放置的状态评估。本文中的检测算法使用多角度建议区域来准确地定位图像中的违规车辆并将其标记在检测到的车辆上。实验数据表明，该算法对监视图像中非法停车的检测具有良好的适应性，有效提高了检查效率。

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