Name
Abstract | ||
|---|---|---|
Automatic detection of underwater objects using side-scan sonar imagery is complicated by the variability of objects, noises, and background signatures. In recent years, as the resolution of side-scan sonar is much higher than before, the sonar imagery can be generated from sonar signal for processing. The first step of underwater object detection Is to segment the underwater objects from sonar imagery. In typical sonar imagery, the object contains two parts: high-light areas (echo) and the shadow behind the object. By analyzing the features of the sidescan sonar imagery, we propose a novel segmentation algorithm for multi-object side-scan sonar imagery. First we utilize a selfadaptive window to scan the imagery and calculate the variance of the window to segment the high-light areas in sonar imagery. Then the shadows of the objects are segmented by fractal dimension. At last, the final segmentation results are achieved by combining the results from the above two steps for further analysis. This segmentation algorithm is based on analyzing the structure of objects in sonar imagery and works well in the multiobject sonar imagery. © 2008 IEEE. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ROBIO.2007.4522495 | 2007 IEEE International Conference on Robotics and Biomimetics, ROBIO |
Keywords | Field | DocType |
Image segmentation,Multiobject,Sonar imagery | Shadow,Computer vision,Side-scan sonar,Object detection,Segmentation,Algorithm,Image segmentation,Sonar,Artificial intelligence,Engineering,Synthetic aperture sonar,Sonar signal processing | Conference |
Volume | Issue | ISSN |
null | null | null |
ISBN | Citations | PageRank |
978-1-4244-1758-2 | 2 | 0.52 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wang Xingmei | 1 | 2 | 0.52 |
| Wang Huanran | 2 | 2 | 0.52 |
| Xiufen Ye | 3 | 42 | 10.31 |
| Zhao Lin | 4 | 2 | 0.52 |
| Wang Kejun | 5 | 2 | 0.52 |