Color Invariant Snakes

Snakes provide high-level information in the form of continuity constraints and minimum energy constraints related to the contour shape and image features. These image features are usually based on intensity edges. However, intensity edges may appear in the scene without a material/color transition to support it. As a consequence, when using intensity edges as image features, the image segmentation results obtained by snakes may be negatively affected by the imaging-process (e.g. shadows, shading and highlights). In this paper, we aim at using color invariant gradient information to guide the deformation process to obtain snake boundaries which correspond to material boundaries in images discounting the disturbing influences of surface orientation, illumination, shadows and highlights. Experiments conducted on various color images show that the proposed color invariant snake successfully find material contours discounting other ”accidental” edges types (e.g. shadows, shading and highlight transitions). Comparison with intensity-based snakes shows that the intensity-based snake is dramatically outperformed by the presented color invariant snake.