Detection Object on Sea Surface to Avoid Collision with Post-Processed in Background Subtraction Image

Alif Akbar Fitrawan, Mohammad Nur Shodiq, Dedy Hidayat Kusuma

Abstract


Data on shipping accident investigations from the National Transportation Safety Committee (NTSC) throughout 2010-2016 of fifty-four accident cases at sea, seventeen of which were accidents caused by collisions on ships in Indonesian waters, act to avoid a collision by detecting an object on the sea surface. Detection object is challenging because so many varieties object on the sea surface. Illumination variations with different seasons, periods, illumination intensity and direction affect the detection of objects directly. A rough sea is seen as a dynamic background of moving objects with size order and shape. All these factors make it difficult to object detection. Therefore, it is possible to conclude that background subtraction on sea surface problem remains open and a definitive robust solution is still missing. In this paper, we have applied a selection of background subtraction algorithms with post-processed to the problem. Experimental results with our dataset verify the high efficiency of our proposed method

Keywords


background subtraction, post-processed; collision avoidance; sea surface

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References


A. Kadar, Pengelolaan Kemaritiman Menuju Indonesia sebagai Poros Maritim Dunia, Jurnal Keamanan Nasional Vol. I, No. 3, 2015.

Simela Victor Muhamad, Indonesia Menuju Poros Maritim Dunia,” Info Singkat Hubungan Internasional, Vol. VI, No. 21, November 2014.

Suyono. Op.Cit, Buku Laporan Direktorat Jenderal Perhubungan Laut, RI Tahun 2014

H. Wang, Z. Wei, S. Wang, C. Ow, K. Ho and B. Feng, AVision-Based Obstacle Detection System for Unmanned Surface Vehicle, in Proc. Int. Conf. Robotics Aut. Mechatronics, 2011, pp. 364–369.

H. Wang, Z. Wei, C. Ow, K. Ho, B. Feng and J. Huang, Improvement in Real-Time Obstacle Detection System for USV, in Proc. Int. Conf. Control, Automation, Robotics & Vision, 2012, pp. 1317–1322.

H. Wang, X. Mou, W. Mou, S. Yuan, S. Ulun, S. Yang, an Bok-Suk Shin. Vision based Long Range Object Detection and Tracking for Unmanned Surface Vehicle. 2015 IEEE 7th International Conference on CIS & RAM

G. Yang, Bo Li, S. Ji, F. Gao, and Q. Xu. Ship Detection From Optical Satellite Images Based on Sea Surface Analysis. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 11, NO. 3 2015

Ruihong Xin, Shaohai Hu, and Shan Ge. Research on Detecting Methods for Sea-Surface Targets. ICSP2006 Proceedings.

V. Bobkov, S. Melman, A. Kudrashov, and A. Scherbatyuk. Vision-based navigation method for a local maneuvering of the autonomous underwater vehicle. 2017 IEEE Underwater Technology (UT)

V.A. Bobkov, A.P. Kudryashov, S.V. Melman, and V.P. May. Image-Based Navigation of Autonomous Underwater Robot and 3d Reconstruction of Environment. 2018 3rd Russian-Pacific Conference on Computer Technology and Applications (RPC).

JIA Yun, DING Yan, LIU Ze-ping. Study on improved arithmetic of image segmentation. Optical technique, 2005, 155-157.

Xie Xiaozhu, Hong Jingxin, Xiao Sixing. Effective Method for Moving Objects Detection on Sea Surface.IEEE Computer Society 2008.

Xiaoqi Li, Weixin Xie, Lixia Wang, and Jihong Pei. Ship Detection Based on Surface Fitting Modeling for Large Range Background of Ocean Images. ICSP2016 IEEE.

Zuohuan Chen, Jiayuan Yang, Zhining Chen and Zhen Kang. Ship Target Detection Algorithm for Maritime Surveillance Video Based on Gaussian Mixture Model. IOP Conf. Series: Journal of Physics: Conf.2018

D. H. Parks and S. S. Fels, "Evaluation of Background Subtraction Algorithms with Post-Processing," 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance(AVSS), vol. 00, no. , pp. 192-199, 2008.

COLREGS. (1972). International Regulations for Prevention of Collisions at Sea, 1972. International Maritime Organization (IMO).




DOI: http://dx.doi.org/10.30630/joiv.3.2.207

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