polygon decomposition based on the straight line skeleton
We propose a novel type of decomposition for polygonal shapes. It is thought that, for the task of object recognition, the human visual system uses a part-based representation. Decompositions based on skeletons have been previously proposed in computer vision. Our method is the first one, however, based on the straight line skeleton. Compared to the medial axis, the straight line skeleton has a few advantages: it contains only straight segments and has a lower combinatorial complexity. The skeletal nodes and the way they are generated are the basis for our decomposition, which has two stages that result in a decomposition into (possibly overlapping) parts. First, a number of visually striking parts are identified, then their boundaries are successively simplified, by locally removing detail. Our method runs in time ((n+r 1 +r 2 2 )log 2 n) , after the skeleton construction, where n is the number of vertices in the polygon, r 1 the number of split events, and r 2 the number of reflex edge annihilations. The decomposition is invariant to rigid motions and uniform scalings. We present results indicating that it provides plausible decompositions for a variety of shapes. This makes it attractive for partial shape matching in content-based image retrieval.
polygonal decomposition straight line skeleton