Angular map-driven snakes with application to object shape description in color images

We propose a method for shape description of objects in color images. Our method employs angular maps in order to identify significant changes of color within the image, which are then used to drive snake models. To obtain an angular map, the angle values of the vectors corresponding to color image pixels are first computed with respect to a reference vector, and organized in a two-dimensional matrix. To identify significant color changes within the original image, the edges of the angular map are next extracted. The resulting edge map is then presented to a snake model. Distance and gradient vector flow snake models have been employed in this work. Experimental results show, not only that the resulting object shape descriptions are accurate and quite similar, but also that our method is computationally efficient and flexible.