Fast range image segmentation by an edge detection strategy

This paper presents an edge-based segmentation technique that allows to process quickly very large range images. The proposed technique consists of two stages. First, a binary edge map is generated; then, a contour detection strategy is responsible for the extraction of the different boundaries. The first stage generates a binary edge map based on a scan line approximation technique. There is a difference with the previous techniques, as only two orthogonal scan line direction are considered. The planar curves defined by the elements contained in each scan line are approximated by oriented quadratic curves. The representative points from each curve are used to define a binary edge map. The second stage is a new approach to the classical contour extraction problem. It shows a difference with the previous approaches which use the enclosed surface information; with the suggested technique, boundaries are obtained by using only the information contained in the binary edge map. It consists in linking the edge points by applying a graph strategy. Experimental results with large panoramic range images are presented.