IOT Based No-parking Notifier System

Gowda, Sanjith. M.; Sushanth, G.; Sujatha, S.

doi:10.1109/i-smac.2018.8653775

Cited by 1 publication

(1 citation statement)

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“…In this study, ANPR was applied to recognize the license plates of parked vehicles; this system already exists in several countries. Many studies have been implemented to evaluate this new monitoring system, such as for vehicle detection in parking areas [1] and machine vision for moving object detection [2], [3], [4], vehicle license-plate detection [5], [6], [7], face recognition to open or close a parking gate [8], smart parking [9], and management and monitoring of parking lots [10]; however, few studies have discussed restricted parking zones [11], [12]. The ANPR system for license plate recognition has not yet been used for vehicles in Indonesia, so the license plate data used is standardized for foreign plates.…”

Section: Introductionmentioning

confidence: 99%

Vehicle License Plate Detection for Parking Offenders Using Automatic License-Plate Recognition

Pratama¹,

Aulia²,

Ramadan³

et al. 2020

Journal of Southwest Jiaotong University

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Vehicles parked illegally on the highway can limit road space and result in congestion. Thus, illegal parking must be monitored and controlled. In this study, a prototype system for detecting the license plates of parking offenders based on image processing was implemented. The first stage in this system is detecting the license plate, then segmenting each character into a separate image. The next stage is converting the character from image to text format, referred to as automatic license-plate recognition. The goal is to send that detected plate license to the database of the authorities, so that the authorities can discover the identity of the parking offender to impose sanctions. In this study, several conditions of acquisition and variations of edge detection methods were tested. Based on the test results, an accuracy rate of 100% was obtained for license plate detection using the Canny method during the morning, with the camera position at 3 meters high, 2 meters of distance, and a 60o angle.

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