Small Bottom Object Density Analysis from Side Scan Sonar Data by a Mathematical Morphology Detector

摘要

This paper describes a system for estimating the local density of small objects on the sea floor by exploiting a robust, non-parametric detector for high resolution images acquired by side scan sonar sensors. Low grazing angle target images are characterised by an area of strong intensity, the highlight, close to an area, the shadow, at the sensor noise level. The detector makes use of mathematical morphology to detect the highlight and the shadow areas within the image, and a fusion scheme to reduce the false alarms due to the sea floor disturbance by declaring a target acquired if an highlight is close to a shadow. Results on data sets collected in the Ligurian and Baltic Sea are reported and discussed.