Object Detection In Underwater Acoustic Images Using Edge Based Segmentation Method

Image segmentation techniques play a vital role in partitioning the image into segments. These techniques are used for detecting the objects in the images. The real challenge in the acoustic image segmentation lies in differentiating the sea floor, sediments and the objects. Due to the typical characteristics and low resolution of the acoustic images, segmentation techniques such as region based, morphological based and edge based methods are not suitable. The sediments will also be traced along with the objects that makes the detection process a very difficult one. In this research paper, edge based segmentation method that uses the morphological operations for identifying the edges followed by a object tracing algorithm is proposed. The images used in this work are captured in real time using Edgetech 4125 Side scan sonar device. The acoustic images are first pre-processed using Wiener and Median filters and a morphological gradient is obtained by subtracting the morphologically dilated and eroded image. Next the edge map of the acoustic images are obtained using binarization method by which the object’s boundary is made visible. Finally a Moore’s object tracing algorithm is used for detecting the objects in the images.