Detection and Simulation of Vacant Parking Lot Space Using EAST Algorithm and Haar Cascade

Abstract

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.