Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8879
Title: A probability-based multi-measure feature matching method in map conflation
Authors: Tong, X
Shi, W 
Deng, S
Issue Date: 2009
Publisher: Taylor & Francis
Source: International journal of remote sensing, 2009, v. 30, no. 20, p. 5453-5472 How to cite?
Journal: International journal of remote sensing 
Abstract: This paper presents a probability-based multi-measure feature matching method in map conflation. Feature matching is used to determine the corresponding features in different datasets that represent analogous entities in the real world. In the proposed method, a total matching probability is computed by the weighted average of multiple measures, including positional measure, shape measure, directional measure and topological measure. The matching strategies for point features, linear features and areal features are also provided. The proposed method is implemented in a prototype for matching features from two different data sources, and is compared with traditional methods. The results demonstrate not only the practicability of using the proposed method to resolve feature matching issues in map conflation, but also its advantages compared with traditional methods in terms of matching effects.
URI: http://hdl.handle.net/10397/8879
ISSN: 0143-1161
EISSN: 1366-5901
DOI: 10.1080/01431160903130986
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