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 manmade 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.