Real Time Detection and Segmentation of Reflectionally Symmetric Objects in Digital Images

Symmetry is a salient visual feature of many man-made objects. This paper describes research into the detection and segmentation of reflectionally symmetric objects in digital images, without the use of a priori object models. The detection method does not assume uniform object colour or texture, and does not rely on prebuilt models such as 3D geometric primitives. A novel detection algorithm has been developed to find lines of reflectional symmetry in images. This detection algorithm can operate at 10 frames per second on 640 by 480 pixel images. Using the detected symmetry, objects are segmented with a dynamic programming approach. Both algorithms have been extended to accommodate skew symmetry