A Two-Stage Framework for Polygon Retrieval Using Minimum Circular Error Bound

Lun Hsing Tung, Irwin King

Abstract: We have proposed a two-stage framework for polygon retrieval [12, 11] which incorporates both qualitative and quantitative measures of polygons in the first and second stage respectively. In this paper, we introduce an extension to our two-stage framework. We propose a new polygon matching technique using Circular Error Bound and describe how this technique works under translation and scaling of polygons. Base on this technique, we propose a new translation invariant similarity measure for polygons named Minimum Circular Error Bound, which can be used in the second stage of the two-stage framework. We compare the Minimum Circular Error Bound method with the Hausdorf Distance method and demonstrate the advantages of our method.