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.

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

• 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