Identification of segmented sedimentary objects in underwater objects using Image processing techniques with SBP data

Abstract

Side Imaging Sonar is mainly used in underwater research effectively in constructing an image of huge areas in the seabed. Image segmentation method acts as a significant responsibility in categorizing an image into various segments. Nevertheless, many of the researchers found that detection of underwater objects applicable through side imaging sonar images and also focused on classification of drowning wreck, airplane etc. This survey designed at distinguishing metal mine objects namely rock or mine as well as segmentation of objects under the seabed (100m distance) to sub-surface. The watershed segmentation along with markers techniques can be carried out for segmenting the input image in sedimentary to generate different regions such as rock, mud, mine, clay etc. Moreover, the detection of sub bottom profiling system can be recognized using Chirping, Boomer, and Pinger sub bottom profiler data for finding frequency range, depth and vertical resolution towards the sub-surface. The acoustics images are primarily preprocessed using the filters such as mean filter, median filter and Laplacian to give attention to intensity changes in every region, finding continuous region i.e local gradient for making the edges thin in underwater surroundings