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Wei-Horng Yeh and Ye-In Chang
Department of Computer Science and Engineering
National Sun Yat-Sen University
Kaohsiung, 804 Taiwan
E-mail: changyi@cse.nsysu.edu.tw
The goal of similarity retrieval is to retrieve images that are similar to query image.
Good access methods for large image databases are very important for efficient retrieval.
The 2D B-string-based and unique-ID-based signature methods can provide four kinds
of similarity retrieval, object and type-i, where 0 <= i <= 2, and can distinguish 169 spatial
relationships. However, 169 spatial relationships are still not sufficient to show all kinds
of spatial relationships between any two objects in 2D space, such as directional relationships,
like north. Moreover, most of the previous similarity retrieval methods, for the
sake of simplicity, apply the MBRs of two objects to define the spatial relationship between
them. The topological relationships, however, between objects can be quite different
from the spatial relationship between their respective MBRs. Therefore, in this
paper, we propose a new method that focuses on the above two problems. To solve the
first problem, we add 9 directional relationships to the 169 spatial relationships. In this
way, we can distinguish up to 289 spatial relationships in 2D space. To handle the second
problem, we apply the concept of topological relationships in our proposed method.
Based on the results of our simulation study, we show that our method can achieve a
higher correct match rate than the 2D B-string-based and unique-ID-based signature
methods can.
Received August 5, 2003; revised October 7, 2004 & February 15, 2005; accepted August 15, 2005.
Communicated by Suh-Yin Lee.
* This research was supported in part by the National Science Council of Taiwan, R.O.C., under grant No. NSC
87-2213-E-110-014.