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標題: Similarity retrieval based on group bounding and angle sequence matching in shape database systems
作者: Huang, P.W.
Dai, S.K.
Lin, P.L.
Kuo, R.T.
關鍵字: similarity retrieval;shape database;string matching;CPA-string;group;bounding;image database;knowledge representation;strings
Project: Journal of Systems and Software
期刊/報告no:: Journal of Systems and Software, Volume 54, Issue 1, Page(s) 9-16.
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. (C) 2000 Elsevier Science Inc. All rights reserved.
ISSN: 0164-1212
DOI: 10.1016/s0164-1212(00)00022-4
Appears in Collections:理學院

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