Please use this identifier to cite or link to this item:
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
image database
knowledge representation
期刊/報告no:: Journal of Systems and Software, Volume 54, Issue 1, Page(s) 9-16.
摘要: 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
Appears in Collections:理學院



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.