Coupled curve evolution equations for ternary images in sidescan-sonar images guided by Lamé curves for object recognition

This paper proposes a new level set segmentation method which is guided by a parametric prior force based on Lamé curves. The use of prior knowledge is advantageous in order to improve the segmentation results in terms of matching expected object types because one can in general state that for different applications some shapes are more likely than others. By avoiding complex shape training processes the level set idea is extended with a parametric prior shape which forces the level set evolution to propagate towards the desired objects by not overpowering the image properties. Also a cross talk evolution is discussed for ternary images to handle correlations between adjacent or correlated objects.