Variable-Scale Smoothing and Edge Detection Guided by Stereoscopy

It is typical in edge detection applications to examine a single scale or to consider some space of scales in the image without knowing which scale is appropriate for each location in the image. However, many images contain a wide variation in the distance to the scene points, and thus objects of the same size can appear at greatly di ering scales in the image. We present a method where the scale of the smoothing and edge detection is varied locally according to the distance to the scene point, which we estimate through stereoscopy. The edges that are detected are thus at the same scale in the world, rather than at the same scale in the image. This method has been implemented e ciently by smoothing the image at a discrete set of scales and performing interpolation to estimate the response at the correct scale for each pixel. The application of this technique to an ordnance recognition problem has resulted in a considerable improvement in performance.