An Efficient Edge Detection Technique Using Filtering and Morphological Operations for Underwater Acoustic Images

Segmentation techniques have received great attention for object detection in image processing and it uses the edge detection as a vital step. Edge detection methods aim at identifying points in an image at which the image brightness changes sharply. There are recent methods that are employed for detecting the edges in digital images which do not suit for low resolution underwater acoustic images. For detecting the edges in the acoustic images, a method which uses wiener filtering followed by median filtering for smoothing and morphological image processing techniques is proposed. The morphological dilation finds the local maximum value and morphological erosion determines the local minimum value in an image. The difference between the dilated image and eroded image gives the morphological gradient. The final edge map is obtained by applying the binarization method to the gradient image. The resultant image has pixel values with increased contrast intensity in the close neighborhood. The edge map shows better performance with respect to the results of the conventional edge detection techniques such as Sobel and Canny.