Similarity retrieval based on group bounding and angle sequence matching in shape database systems

Abstract In this paper, a new method for retrieving similar shapes from a shape database is proposed. The shapes in the database are indexed by their CPA-strings. When a query shape is submitted to the system, it is converted to a CPA-string from which both the lower and the upper bounds of the locations of the potentially matched shapes are computed. This will restrict the search space to a reasonable small proportion of the whole database. At the second stage, an angle sequence matching algorithm is invoked to compute the Weighted Levensthein Distances between the query CPA-string and the selected database CPA-strings. The shapes that have distances less than a given threshold are finally retrieved. Experimental results show that our approach is robust, accurate and efficient in terms of finding the desired shapes within a reasonable time, even if the shapes are rotated, scaled, and may have boundary noise.