GEDContours: A High Speed Contour Detector for Grayscale Images

We propose a high-speed contour detector for grayscale images that works by combining the edge segments produced by Edge Drawing (ED) algorithm at multiple scales, thus the name GEDContours. Unlike most contour detectors, which return soft binary contour maps, GEDContours returns its result as a set of edge segments, each a contiguous chain of pixels. We evaluate the performance of GEDContours in the context of the RUG dataset, which has 40 grayscale images each of size 512x512 with human annotated ground truth contours, and compare its results with some of the best contour detectors found in the literature using the F-score metric. Experimental results show that GEDContours is among the best contour detectors with an overall F-score of 0.7011 on the RUG dataset, and takes an average of just 0.42 seconds as opposed to 74 seconds for the global Probability of boundary ultrametric contour maps (gPb-ucm) with an overall F-score of 0.7051, and 125 seconds for the sparse code gradients (scg) with an overall F-score of 0.6997. Due to its good performance and blazing speed, we believe that GEDContours will be very useful for high speed image processing and computer vision applications.