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Sea-Sky-Line/Coastline Extraction in Infrared Imagery Based on Structure Tensor and Hough Transform

Yongsong Li1,2, Zhengzhou Li1,2,3, Weiqi Xiong1,2, and Jiangpeng Yu1,2
1.School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China
2.Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044, China
3.Key Laboratory of Beam Control, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
Abstract—Sea-sky-line/coastline extraction is a key problem in infrared maritime target search and track systems. However, the current studies of sea-sky-line/coastline detection in infrared imagery usually aim for detection accuracy or time saving unilaterally, and it is seldom suitable for practical applications in complex scenarios. To cope with this problem, a novel sea-sky-line/coastline extraction method based on the structure tensor and Hough transform is proposed in this paper. Firstly, the Gaussian filter based pre-processing is applied on the infrared image to eliminate the clutters. Then, the Gaussian structure tensor is proposed to enhance the line property of sea-sky-line/coastline and a segmentation threshold is selected to binarize the image. Finally, on the basis of line property of sea-sky boundary in binary image, the Hough transform is applied to effectively locate the sea-sky-line/coastline. Extensive experiments show that the proposed sea-sky-line/coastline extraction method not only has an outstanding detection accuracy under different scenarios but also has the potential of real-time hardware processing. 

Index Terms—sea-sky-line/coastline extraction, infrared imagery, structure tensor, Hough transform

Cite: Yongsong Li, Zhengzhou Li, Weiqi Xiong, and Jiangpeng Yu, "Sea-Sky-Line/Coastline Extraction in Infrared Imagery Based on Structure Tensor and Hough Transform," International Journal of Signal Processing Systems, Vol. 7, No. 4, pp. 123-128, December 2019. doi: 10.18178/ijsps.7.4.123-128

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