Author(s)

John DeCatrel

Abstract

This paper reports extensions to an innovative object detection and pose estimation method for non-analytic shapes, potentially useful to machine or robotic vision systems. Recently we demonstrated a shape-invariant recognition technique based upon the generalized Hough transform that is invariant to large planar changes in object position and rotation, as well as small changes in scale. The method works even for cases where objects are moderately occluded. It is of comparatively low complexity (O(n2)), where n is the edge length in pixels. The original technique has now been extended to detect and report large scale changes and multiple instances of the transformed prototype. Preliminary results have been obtained and are demonstrated. These improvements do not increase the original time complexity. Ha

Keywords