Graph extraction from color images

Abstract. An approach to symbolic contour extraction will be described that consists of three stages: enhancement, detection, and extraction of edges and corners. Edges and corners are enhanced by models of monkey cortical complex and end-stopped cells. Detection of corners and local edge maxima is performed by selection of local maxima in both edge and corner enhanced images. These maxima form the anchor points of a greedy contour following algorithm that extracts the edges. This algorithm is based on an idea of spatially linking neurons along the edge that will fire in synchrony to indicate an extracted edge. The extracted edges and detected corners represent the symbolic representation of the image. The advantage of the proposed model over other models is that the same low constant thresholds for corner and local edge maxima detection are used for different images. Closed contours are guaranteed by the contour following algorithm to yield a fully symbolic representation which is more suitable for reasoning and recognition. In this respect our methodology is unique, and clearly different from the standard edge detection methods.