교통 영상 정보에 변화 탐지 기법 적용을 통한 교통량 분석 기법에 관한 연구
A Study on the Traffic Flow Analysis Method based on Change Detection for Traffic Video Data
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초록
최근 차량 수가 증가함에 따라 교통 문제가 더욱 심각해지고 있다. 정확한 교통 흐름 분석은 도로 계획에 중요하며 지능형 교통 시스템에 필수적인 요소이다. 그러나 기존의 교통량 분석 기술은 일반적으로 실시간 처리가 아니며 수 분 이상의 배치성 작업을 기반으로 처리하고 있다. 또한, 차량 그림자, 건물, 공장 길가 등과 같은 외부 조건에 의해 쉽게 영향을 받는다. 본 논문에서는 이미지 등록, 노이즈 제거, 배경 등 변화 탐지를 기반으로 한 새로운 교통량 분석 기법을 제시한다. 본 논문의 변화탐지 기반 교통량 분석 기술은 실시간으로 처리가 가능하고 외부 환경 변화에 강인한 특성이 있다.
Abstract
Traffic problems are becoming more serious as the number of vehicles increases. Accurate traffic flow analysis is critical to road planning and is an integral part of intelligent transportation systems. However, existing traffic analysis techniques are not usually real-time processing, but are based on batch-based operations for several minutes or more. It is also easily affected by external conditions such as vehicle shadows, buildings, factory roads, and so on. In this paper, we propose a new traffic analysis method based on image registration, noise removal, and background detection. The change detection based traffic volume analysis technique of this paper is able to process in real time and is robust to external environment change.
참고문헌 (13)
- BAS, Erhan, "Automatic vehicle counting from video for traffic flow analysis", Intelligent Vehicles Symposium, 2007 IEEE, pp.392~397 (2007)
- L. V. Yisheng, "Traffic flow prediction with big data: A deep learning approach", IEEE Trans. Intelligent Transportation Systems, 16(2), pp.865~873 (2015)
- Calvert, Simeon, "Road Vehicle Automation 4", pp.235~245 (2018), Springer
- Peng, Yanan, "Traffic flow detection and statistics via improved optical flow and connected region analysis", Signal, Image and Video Processing, 12(1), pp.99~105 (2018)
- Caceres, Noelia, "Traffic flow estimation models using cellular phone data", IEEE Transactions on Intelligent Transportation Systems, 13(3), pp.1430~1441 (2012)
- K. E. Ruimin, "Real-time bidirectional traffic flow parameter estimation from aerial videos", IEEE Transactions on Intelligent Transportation Systems, 18(4), pp.890~901 (2017)
- Gong, Maoguo, "Fuzzy clustering with a modified MRF energy function for change detection in synthetic aperture radar images", IEEE Transactions on Fuzzy Systems, 22(1), pp.98~109 (2014)
- Gu, Wei, "Change detection method for remote sensing images based on an improved Markov random field", Multimedia Tools and Applications, 76(17), pp.17719~17734 (2017)
- Dunn, Joseph C., "A fuzzy relative of the ISODATA process and its use in detecting compact wellseparated clusters" (1973)
- Bezdek, James C., "Objective function clustering. In:Pattern recognition with fuzzy objective function algorithms", pp.43~93 (1981), Springer
- Lei, Tao, "Unsupervised Change Detection Using Fast Fuzzy Clustering for Landslide Mapping from Very High-Resolution Images", Remote Sensing, 10(9), pp.1381~ (2018)
- Mishra, Niladri Shekhar, "Fuzzy clustering algorithms incorporating local information for change detection in remotely sensed images", Applied Soft Computing, 12(8), pp.2683~2692 (2012)
- Bay, Herbert, "Surf: Speeded up robust features", European conference on computer vision, pp.404~417 (2006), Springer