Computational Geometry of Contour Extraction

We present a method for extracting contours from digital images using techniques from computational geometry. Our approach is different from traditional pixelbased methods in image processing. Instead of working directly with pixels, we extract a set of oriented feature points from the input digital images, then apply classical geometric techniques such as clustering, linking, and simplification to find contours among these points. Experiments on synthetic and natural images show that our method can effectively extract contours even from images with considerable noise; moreover the extracted contours have a very compact representation.