Abstract
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.
Highlights
Unmanned surface vehicles (USVs) eliminate risk and are a cost-saving tool for maritime applications in the surface zone
We propose an efficient waterline detection method based on structure extraction and texture analysis with respect to optical images and present a practical application to a USV
We present an efficient waterline detection based on structure extraction and atexture of position andoptical features such aswhich color,was brightness, texture similar to thatapplication of small region of analysis with images, validated through practical in a composed
Summary
Unmanned surface vehicles (USVs) eliminate risk and are a cost-saving tool for maritime applications in the surface zone. The requirements of optical sensors such as the experimental environment, operating cost, and equipment cost are all quite low [11,12,13] Because of their advantages of direct and real-time imaging capability, optical technologies have been used to detect obstacles, achieve real-time vision feedback, and help improve the precision and efficiency of mobile robots. (2) The application area of current waterline detection methods based on optics is limited [14]; several studies have considered waterline detection by using optical images, the sailing environments of the mobile robots are simple; for example, irregularly shaped reference objects may be required, or the shape of the entire waterline can be approximated by a straight line; when the system is in an unknown outdoor environment, it is difficult for these requirements to be fulfilled.
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