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YOLO와 EasyOCR을 혼합한 차량 번호 기반 겸용 차량 분류 연구 A Study on Vehicle Number-Based Combined Vehicle Classification Using YOLO and EasyOCR

이경수, 임병철, 윤득선
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한국기계기술학회지 (韓國機械技術學會誌)
제26권 제5호 (2024.10)
pp.982-986
한국기계기술학회 (Korean Society of Mechanical Technology)
초록

The lane designation and the bus-only lane system for traffic speed and road safety are difficult to crack down on, and for this purpose, crackdown methods using image recognition technologies are being studied. Existing studies require continuous learning or additional equipment, and it is difficult to classify combined vehicles such as vans and pickup trucks. Therefore, in this study, YOLO and EasyOCR were mixed to classify combined vehicles through vehicle type symbols. For combined vehicles, higher accuracy was shown than classification using YOLO. Due to the nature of Hangul, the accuracy was slightly lowered because the OCR was not accurately recognized, but if it is used with the existing YOLO classification, high accuracy of crackdown will be possible.

키워드
광학 문자 인식영상 인식화물차량차량 번호판차종 분류겸용 차량딥러닝 YOLO(You Only Look Once)OCRImage RecognitionCargo VehicleLicense PlateClassification of Vehicle TypesCombined VehicleDeep learning
목차
Abstract
1. 서 론
2. 연구 내용
    2.1 차량 번호판 조사
    2.2 데이터 수집
    2.3 연구 방법
    2.4 연구 결과
3. 결 론
후 기
References
저자
  • 이경수(Researcher, Automotive Semiconductor and Sensor R&D Dept., Korea Automotive Technology Institute) | K. S. Lee Corresponding author
  • 임병철(Senior Researcher, Automotive Semiconductor and Sensor R&D Dept., Korea Automotive Technology Institute) | B. C. Yim
  • 윤득선(Executive Principal Researcher, Automotive Semiconductor and Sensor R&D Dept., Korea Automotive Technology Institute) | D. S. Yun