Browse > Article
http://dx.doi.org/10.9717/kmms.2012.15.11.1284

Multiple Ship Object Detection Based on Background Registration Technique and Morphology Operation  

Kim, Won-Hee (부경대학교 IT융합응용공학과)
Arshad, Nasim (부경대학교 전자공학과)
Kim, Jong-Nam (부경대학교 IT융합응용공학과)
Moon, Kwang-Seok (부경대학교 전자공학과)
Publication Information
Journal of Korea Multimedia Society / v.15, no.11, 2012 , pp. 1284-1291 More about this Journal
Abstract
Ship object detection is a technique to detect the existence and the location of ship when ship objects are shown on input image sequence, and there are wide variations in accuracy due to environmental changes and noise of input image. In order to solve this problem, in this paper, we propose multiple ship object detection based on background registration technique and morphology operation. The proposed method consists of the following five steps: background elimination step, noise elimination step, object standard position setting step, object restructure step, and multiple object detection steps. The experimental results show accurate and real-time ship detection for 15 different test sequences with a detection rate of 98.7%, and robustness against variable environment. The proposed method may be helpful as the base technique of sea surface monitoring or automatic ship sailing.
Keywords
Background Registration; Morphology Operation; Ship Detection;
Citations & Related Records
연도 인용수 순위
  • Reference
1 F. Porikli, "Achieving Real-Time Object Detection and Tracking Under Extreme Conditions," Journal of Real-time Image Processing, Vol. 1, No. 1, pp. 33-40, 2006.   DOI
2 L. Vibha, M. Venkatesha, P.G. Rao, N. Suhas, P.D. Shenoy, K.R. Venugopal, and L.M. Patnaik, "Moving Vehicle Identification using Background Registration Technique for Traffic Surveillance," International Multi-Conference of Engineers and Computer Scientists, Vol. 1, pp. 19-21, 2008.
3 J. Cezar Silveira Jacques, C. Rosito Jung, and S. Musse, "Background Subtraction and Shadow Detection in Grayscale Video Sequences," Proc. of the XVIII Brazilian Symposium on Computer Graphics and Image Processing, pp. 189-197, 2005.
4 Z. Wei, D. Lee, D. Jilk, and R. Schoenberger, "Motion Projection for Floating Object Detection," Proc. of the 3rd International Conference on Advances in Visual Computing, Vol. 2, pp. 152-161, 2007.
5 A. Khashman, "Automatic Detection, Extraction and Recognition of Moving Objects," International Journal of Systems Applications Engineering & Development, Vol. 2, Issue 1, pp. 43-51, 2008.
6 W. Li, K. Yang, J. Chen, Q. Wu, and M. Zhang, "A Fast Moving Object Detection Method via Local Neighborhood Similarity," Proc. of the 2009 IEEE International Conference on Mechatronics and Automation, pp. 4500-4505, 2009.
7 F. Bi, B. Zhu, L. Gao, and M. Bian, "A Visual Search Inspired Computational Model for Ship Detection in Optical Satellite Images," IEEE Geoscience and Remote Sensing Letters, Vol. 9, No. 4, pp. 749-753. 2012.   DOI
8 A. Monnet, A Mittal, N. Paragios, and V. Ramesh, "Background Modeling and Subtraction of Dynamic Scenes," Proc. ICCV 2003, pp. 1305-1312, 2003.
9 A. Elgammal, D. Harwood, and L.S. Davis, "Non-parametric Model for Background Subtraction," Proc. ECCV 2000, pp. 751-767, 2000.
10 B.D. Lucas and T. Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision", Proc. of Image Understanding Workshop, pp. 121-130. 1981.
11 김낙빈, "형태학적 연산을 이용한 운송 컨테이너 영상의 문자 분할," 한국멀티미디어학회논문지, Vol. 2, No. 4, pp. 390-399, 1999.