基于EAST算法和Haar级联的停车场空置空间检测与仿真

Rizki Alfarizi Harahap, Eri Prasetyo Wibowo, Robby Kurniawan Harahap
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引用次数: 4

摘要

经常因寻找空车位而造成的时间损失是车辆使用者不希望发生的事情。本文讨论了如何制作仿真软件来提供可用停车位的信息。使用的方法包括使用EAST文本检测器算法进行字符识别,使用Haar级联分类算法进行车辆检测,以及使用空闲停车位检测。本研究提出了一种利用特征文本检测车位内车辆的检测器。然后将这三种方法组合成一个仿真系统。本研究使用Python和OpenCV库作为仿真工具。模拟使用60秒的视频流运行,然后每10秒观察一次结果。结果表明,该信息可以以包含可用车位的文本形式出现。该仿真系统可以方便地对停车区域进行监控,主要针对空置车位,使停车系统更高效地进行停车管理。
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Detection and Simulation of Vacant Parking Lot Space Using EAST Algorithm and Haar Cascade
Frequent loss of time caused by finding a vacant parking space is an undesirable event by vehicle users. This paper discusses making simulation software that can provide information about available parking spots. The methods used include character recognition with the EAST text detector algorithm, vehicle detection with the Haar cascade classification algorithm, and Detection of vacant parking spots. This research presents a detector using feature text to detect vehicles in parking slots. The three methods are then combined into a simulation system. Python and OpenCV libraries are used as simulation tools in this research. The simulation runs using 60 seconds of video-stream, then observes the results every 10 seconds. The results obtained that the information can appear in the form of a text containing the available parking slots. This simulation system can facilitate the monitoring of parking areas, mainly for vacant parking slots, and make parking systems more efficient for parking management.
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