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
- 학술저널
- 저자정보
- 저널정보
- 한국마린엔지니어링학회 Journal of Advanced Marine Engineering and Technology (JAMET) 한국마린엔지니어링학회지 제41권 제5호
- 발행연도
- 2017.6
- 수록면
- 439 - 444 (6page)
- DOI
- 10.5916/jkosme.2017.41.5.439
이용수
초록· 키워드
오류제보하기
It is very important to detect exactly objects in object tracking systems such as safety and surveillance systems. In this paper, we introduced a method to track random objects using the OpenCV library and Visual C++ program. In random object tracking systems, we cannot calculate the exact distance and bias angle between the object and the system. To solve this problem, we used the center of the object image to build a fuzzy logic controller to control the system in order to determine the required position of the object image. Because this system uses an autofocus camera, the area of the object image also affected the bias angle between the target and the system. Thus, in our system, the center and area of the object image were used to build the fuzzy logic controller. To improve the quality of the object tracking system, the CAMSHIFT algorithm was used. With the CAMSHIFT algorithm, a target can be detected by isolating its color and following the tracking window in order to distinguish the target from the other objects, even though these objects have the same color as the target.
목차
Abstract
1. Introduction
2. CAMSHIFT algorithm
3. Fuzzy logic controller
4. Random object tracking system and experiment result
5. Conclusion
References
참고문헌 (10)
참고문헌 신청
G. Bradski and A. Kaehler “Learning OpenCV computer vision with the OpenCV library,” O’Reilly, pp. 1-29, 2008.
R. J. Francois, “CAMSHIFT tracker design experiments with intel OpenCV and SAI,” IMSC-04-423, 2004 ARJF
Zhang, Y. Qiao, E. Fallon, and C. Xu “An Improved CamShift Algorithm for Target Tracking in Video Surveillance,” Dublin Institute of Technology, 9th. IT&T Conference, 2009.
P. Hidayatullah and H. Konik, “CAMSHIFT Improvement on Multi-Hue and Multi-Object Tracking,” 2011 International Conference on Electrical Engineering and Informatics 17-19 July 2011.
A. Shalhi and A. Y. Jammoussi, “Object tracking system using Camshift, Meanshift and Kalman filter,” World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 64, no. 4, 2012
R. J. Francois, “CAMSHIFT tracker design experiments with intel OpenCV and SAI,” IMSC-04-423, 2004 ARJF
Zhang, Y. Qiao, E. Fallon, and C. Xu “An Improved CamShift Algorithm for Target Tracking in Video Surveillance,” Dublin Institute of Technology, 9th. IT&T Conference, 2009.
P. Hidayatullah and H. Konik, “CAMSHIFT Improvement on Multi-Hue and Multi-Object Tracking,” 2011 International Conference on Electrical Engineering and Informatics 17-19 July 2011.
A. Shalhi and A. Y. Jammoussi, “Object tracking system using Camshift, Meanshift and Kalman filter,” World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 64, no. 4, 2012
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UCI(KEPA) : I410-ECN-0101-2018-559-001054594