Underwater manmade and archaeological object detection in optical and acoustic data.

We propose a method designed for processing acoustic and optical data producing information about the presence of man-made and archaeological objects lying on the seabed. This method statistically highlights this type of artifacts among surrounding environment, weighting properly the persistence of meaningful curves in a video sequence, or in a sonogram. To this aim, we made use of the ELSD algorithm, a parameterless method inspired by Gestalt principles which has proven to provide promising results.