Advanced Gray-Scale Morphological Filters for the Detection of Sea Mines in side-Scan Sonar Imagery

摘要

Computing Devices Canada, a General Dynamics company, undertakes research in image processing with fous on the automatic reognition of sea mines. This paper presents the use of advanced gray-scale mrphological filters for this function as applied to side scan sonar imagery. Sea mines in side scan sonar imagery can be characterized by a mine-body and a mine-shadow. Mine-bodies consist of bright regions, relative to the background, with a specific shape and size. Mine-shadows consist of dark regions, relative to the background, with a specific shape and size. The shapes and sizes of these regions depende on the mine type, the orientation of the mine, the physical acquisition process of the sonar imagery, and the environmen in which the mine is lcated. Advanced gray-scale morphological filter provide very powerful and robust tools to extract brigth and dark regions with low signal to nose ratio in very noisy imagery using geometric constraints such as shape, size and total surface area. For the detection of sea mines we use these morphological filters with the minimum and maximum geometric constraints for the mine-bodies and mine-shadows. The independent detection of mine-bodies and maximum geometric constraints for the mine-bodies and mine-shadows. The independent detection of mine-bodies and mine-shadows allows the detection of bottom, moored and drifting mines with the same detection algorithm. Consistent mine-body and mine-shadow combinations are resolved nto mine like objects.