Underwater acoustic image segmentation based on deformable template

In order to solve the problem of deformation and blurred edge in underwater acoustic image segmentation, an approach based on the deformable template is presented. Compared with the energy minimization of the Snake model, the energy function is redefined by adding a shape restriction. This improves the noise-resistance ability so that robustness and high segmentation efficiency are acquired. The energy optimization problem is tackled using the Dijkstra Algorithm. This method has been successfully tested on the filled-in acoustic images. The results show that this algorithm is efficient, precise and very immune to image deformation and noise when compared to results obtained from the Snake model and several traditional optimization methods.