지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2014.1
- 수록면
- 181 - 184 (4page)
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초록· 키워드
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Recently, we are developing a video-based traffic surveillance system (TSS). This system provides users with traffic information. Our TSS system consists of lane detection, vehicle detection and classification, and traffic parameter extraction. We use real-time streaming captured from CCTV camera locates at each road. The proposed system first finds lanes on the road using accumulated movements of the vehicles. Then, within road area, it detects vehicle regions among background and recognizes its type as one of five types: sedan, SUV, truck, bus and bike. Finally, traffic parameter is calculated and uploaded to database. Since road scenes are usually degraded, it makes difficult to estimate vehicle’s motion and background accurately.
In this paper, an effective video restoration algorithm is proposed. For higher quality of result a variety of features such as color, blurring, and noise are considered. Images are firstly enhanced using intensity normalization between two consecutive frames. In addition to remove the grain noise, we use the combined filter of Gaussian filter and median filter. The experimental results show that the proposed method is effective at removing the global noise in video and is applicable to the automatic vehicle extraction system.
In this paper, an effective video restoration algorithm is proposed. For higher quality of result a variety of features such as color, blurring, and noise are considered. Images are firstly enhanced using intensity normalization between two consecutive frames. In addition to remove the grain noise, we use the combined filter of Gaussian filter and median filter. The experimental results show that the proposed method is effective at removing the global noise in video and is applicable to the automatic vehicle extraction system.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. TRAFFIC SURVEILLANCE SYSTEM(TSS)
Ⅲ. EXPERIMENTAL RESULTS
Ⅳ. CONCLUSION
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UCI(KEPA) : I410-ECN-0101-2016-530-000944789