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Description

The goal of this work is to provide an empirical basis for research on image segmentation and boundary detection. To this end, we have collected 12,000 hand-labeled segmentations of 1,000 Corel dataset images from 30 human subjects. Half of the segmentations were obtained from presenting the subject with a color image; the other half from presenting a grayscale image. The public benchmark based on this data consists of all of the grayscale and color segmentations for 300 images. The images are divided into a training set of 200 images, and a test set of 100 images. We have also generated figure-ground labelings for a subset of these images which may be found here We have used this data for both developing new boundary detection algorithms, and for developing a benchmark for that task. You may download a MATLAB implementation of our boundary detector below, along with code for running the benchmark. We are committed to maintaining a public repository of benchmark results in the spirit of cooperative scientific progress.