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:2019,28(11):107-114
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基于深度学习的智能停车场车位查询系统
郑志锋1,2,3, 刘金清1,2,3, 施文灶1,2,3
(1.福建师范大学 医学光电科学与技术教育部重点实验室, 福州 350007;2.
福建师范大学 福建省光子技术重点实验室, 福州 350007;3.
福建师范大学 福建省光电传感应用工程技术研究中心, 福州 350007)
Intelligent Parking Space Query System Based on Deep Learning
(1.Key Laboratory of Optoelectronic Science and Technology for Medicine (Ministry of Education), Fujian Normal University, Fuzhou 350007, China;2.
Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350007, China;3.
Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fujian Normal University, Fuzhou 350007, China)
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本文已被:浏览 34次   下载 20
投稿时间:2019-04-22    修订日期:2019-05-20
中文摘要: 本文基于深度学习目标检测算法设计并实现了一种实时的智能停车场车位信息查询系统.采用YOLO目标检测算法结合大量关于汽车以及车牌的图像数据对物体检测模型进行训练.利用该模型对停车场视频监控画面进行处理,根据模型处理的结果以及所设计的相关算法对车位进行判断,并且计算出被占用车位停车时长,识别出车辆的车牌信息.车位信息将以示意图的方式通过微信终端进行接收,使车主能够实时获取停车场车位信息.该系统能够准确地判断出停车场的车位信息,可为城市商业停车场管理方式提供参考.
中文关键词: 深度学习  停车场  车位信息  YOLO  车牌识别
Abstract:This study designs and implements a real-time intelligent parking space information query system based on deep learning object detection algorithm. The model is trained by adopting the YOLO object detection algorithm combined with a large number of vehicle and license plate images. Use the model to process the parking lot surveillance video. According to the results of the model processing and the related design of algorithm, judge the free parking space, calculate the parking time of the occupied parking space and recognize the license plate. The parking information will be received by the WeChat terminal in a schematic way, so that the drivers can obtain the parking information in real time. The system can accurately judge the parking information and provide reference for the management of urban commercial parking lot.
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基金项目:国家自然科学基金青年科学基金(41701491);中央引导地方科技发展专项(2017L3009);福建省基金(2017J01464)
引用文本:
郑志锋,刘金清,施文灶.基于深度学习的智能停车场车位查询系统.计算机系统应用,2019,28(11):107-114
ZHENG Zhi-Feng,LIU Jin-Qing,SHI Wen-Zao.Intelligent Parking Space Query System Based on Deep Learning.COMPUTER SYSTEMS APPLICATIONS,2019,28(11):107-114

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