Abstract
Edge maps, which are computed from textured scenes using existing methods based on local image analysis, are not very meaningful. This is because edges at object boundaries are not differentiated from edges in texture. We introduce a real-time algorithm that overcomes this difficulty by computing the Direchlet integral in a small image patch at different scales. These measurements are combined and interpreted in a probabilistic framework avoiding the need to threshold. As a result, a higher-level process can utilize the output of this algorithm. Texture does not fit our model of a boundary edge thus its presence is detected by the probabilistic model as an outlier. Convincing results are shown on synthetic as well as images of the natural world. This algorithm is intended to be a fast preprocessing step for localizing boundary edges and textured image regions.