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Effective Waterline Detection of Unmanned Surface Vehicles Based on Optical Images

1,2,* and 1
College of Computer Science and Engineering, Northeastern University, Wenhua Str. 3, Shenyang 110819, China
State Key Laboratory of Synthetical Automation for Process Industries, Wenhua Str. 3, Shenyang 110819, China
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Sensors 2016, 16(10), 1590;
Received: 14 July 2016 / Revised: 18 September 2016 / Accepted: 20 September 2016 / Published: 27 September 2016
(This article belongs to the Section Physical Sensors)
PDF [16314 KB, uploaded 27 September 2016]


Real-time and accurate detection of the sailing or water area will help realize unmanned surface vehicle (USV) systems. Although there are some methods for using optical images in USV-oriented environmental modeling, both the robustness and precision of these published waterline detection methods are comparatively low for a real USV system moving in a complicated environment. This paper proposes an efficient waterline detection method based on structure extraction and texture analysis with respect to optical images and presents a practical application to a USV system for validation. First, the basic principles of local binary patterns (LBPs) and gray level co-occurrence matrix (GLCM) were analyzed, and their advantages were integrated to calculate the texture information of river images. Then, structure extraction was introduced to preprocess the original river images so that the textures resulting from USV motion, wind, and illumination are removed. In the practical application, the waterlines of many images captured by the USV system moving along an inland river were detected with the proposed method, and the results were compared with those of edge detection and super pixel segmentation. The experimental results showed that the proposed algorithm is effective and robust. The average error of the proposed method was 1.84 pixels, and the mean square deviation was 4.57 pixels. View Full-Text
Keywords: unmanned surface vehicle (USV); waterline detection; optical image blurring unmanned surface vehicle (USV); waterline detection; optical image blurring

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Wei, Y.; Zhang, Y. Effective Waterline Detection of Unmanned Surface Vehicles Based on Optical Images. Sensors 2016, 16, 1590.

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