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http://dx.doi.org/10.6109/jkiice.2021.25.12.1762

The System of Arresting Wanted Vehicles for Violent Crimes for Public Safety  

Ji, Moon-Se (Department of Software Security, Graduate School of Computer & Information Technology, Korea University)
Ki, Heajeong (Research Institute, Research Institute, Bluecoms Co. Ltd.)
Ki, Chang-Min (Management Supports Department, Bluecoms Co. Ltd.)
Moon, Beom-Seob (Research Institute, Bluecoms Co. Ltd.)
Park, Sung-Geon (Research Institute, Bluecoms Co. Ltd.)
Abstract
The final goal of this study is to develop a system that can analyze whether a wanted vehicle is a criminal vehicle from images collected from black boxes, smartphones, CCTVs, and so on. Data collection was collected using a self-developed black box. The used data in this study has used a total of 83,753 cases such as the eight vehicle types(truck, RV, passenger car, van, SUV, bus, sports car, electric vehicle) and 434 vehicle models. As a result of vehicle recognition using YOLO v5, mAP was found to be 80%. As a result of identifying the vehicle model with ReXNet using the self-developed black box, the accuracy was found to be 99%. The result was verified by surveying field police officers. These results suggest that improving the accuracy of data labeling helps to improve vehicle recognition performance.
Keywords
Smart city; Security; Vehicle information recognition; Public Safety; Criminal vehicle re-identification;
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