야간 차량 영상에서 차량 정보 추출에 관한 연구
A Study on Vehicle Information Extraction from Night Vehicle Image
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참고문헌
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초록
최근의 차량 정보 추출에 관한 연구가 활발히 이루어지고 있다. 차량 정보는 무인 관리 시스템 등 많은 응용 분야가 있으며 대부분 차량 정보 수집 방법은 비 접촉식 방법을 취하고 있다. 본 논문에서는 전조등 영역 정보, 차량 번호판 영역 정보를 추출하는 방법을 제안하고자 한다. 전체 영상에서 이진화를 수행한 후, 크기가 큰 원 영역을 조건 검사를 통하여 전조등 영역으로 추출한다. 차량 번호판 영역 추출 방법은 2단계로 차량 번호판 후보 영역 추출 단계와 차량 후보 영역의 검증 단계로 구성된다. 차량 번호판 후보 영역은 경계선 검출 결과를 이진화하여 군집된 영역을 후보 영역으로 추출한다. 추출된 차량 후보 영역은 전조등 위치를 고려하여 후보 영역 범위를 축소하고, 축소된 범위에서 후보 영역 검증 방법을 이용하여 차량 번호판 영역을 추출한다. 실험결과 차량 전조등 영역 및 차량 번호판 영역의 검출 결과가 좋음을 볼 수 있다. 추출된 전조등 영역은 향후 위법 전조등 검색에 활용할 수 있다.
Abstract
Recently, research on the extraction of vehicle information has been actively conducted. Vehicle information has many applications such as unmanned management system, and most of the methods of vehicle information collection are non-contact method. In this paper, we propose a method to extract headlight area information and license plate area information. After the binarization is performed on the whole image, the large area is extracted to the headlight area through the condition check. The license plate area extraction method consists of two stages: a license plate candidate region extraction step and a vehicle candidate region verification step. The license plate candidate region binarizes the boundary detection result and extracts the clustered region as a candidate region. The extracted candidate region of the vehicle is reduced by considering the position of the headlight and the region of the license plate is extracted by using the candidate region verification method in the reduced range. Experimental results show that the detection results of the vehicle headlight area and the license plate area are good. The extracted headlight area can be utilized in the search for illegal headlights in the future.
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