• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.987-994
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• 2018

In this paper, an automatic transmission system of traffic information is presented. Here, a traffic event is defined as an obstacle to an emergency vehicle such as an ambulance or a fire truck. When a traffic event is detected from a video recorded by a black box installed in a vehicle, the implemented system automatically transmits a proof image and corresponding information to the control center through an e-mail. For this purpose, we realize an algorithm of identifying the numbers and a character from the license plate, and an algorithm for determining the occurrence of a traffic event. To report the event, a function for automatic transmission of the text and image files through e-mail and file transfer protocol (FTP) is also appended. Therefore, if the traffic event is extended and applied to the presented system, it will be possible to establish a convenient reporting system for the violation of various traffic regulations. In addition, it will contribute to significantly reduce the number of traffic violations against the regulations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.93-104
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• 2023

Currently, the permanent road traffic volume surveys under Road Act are conducted using a intrusive Automatic Vehicle Classification (AVC) equipments to classify 12 categories of vehicles. However, intrusive AVC equipment inevitably have friction with vehicles, and physical damage to sensors due to cracks in roads, plastic deformation, and road construction decreases the operation rate. As a result, accuracy and reliability in actual operation are deteriorated, and maintenance costs are also increasing. With the recent development of ITS technology, research to replace the intrusive AVC equipment is being conducted. However multiple equipments or self-built DB operations were required to classify 12 categories of vehicles. Therefore, this study attempted to prepare a method for classifying 12 categories of vehicles using vehicle specification information of the Vehicle Management Information System(VMIS), which is collected and managed in accordance with Motor Vehicle Management Act. In the future, it is expected to be used to upgrade and diversify road traffic statistics using vehicle specifications such as the introduction of a road traffic survey system using Automatic Number Plate Recognition(ANPR) and classification of eco-friendly vehicles.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.447-454
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• 2013

As the surveillance CCTVs are increasing every year, big data image processing for the CCTV image data has become a hot issue. In this paper, we propose a Hadoop-based big data image processing technique to recognize a vehicle number from a large amount of automatic number plate images taken from CCTVs. We also implement the vehicle route tracking system that displays the moving path of the searched vehicle on Google Maps with the related information together. In order to evaluate the performance we compare and analysis the vehicle number recognition time for a lot of CCTV image data in Hadoop and the single PC environment.