ISSN:
1573-7624
Keywords:
geographical image retrieval
;
multi-resolution wavelet transform
;
texture features
;
hierarchical clustering
Source:
Springer Online Journal Archives 1860-2000
Topics:
Geography
Notes:
Abstract Current retrieval methods in geographic image databases use only pixel-by-pixel spectral information. Texture is an important property of geographical images that can improve retrieval effectiveness and efficiency. In this paper, we present a content-based retrieval approach that utilizes the texture features of geographical images. Various texture features are extracted using wavelet transforms. Based on the texture features, we design a hierarchical approach to cluster geographical images for effective and efficient retrieval, measuring distances between feature vectors in the feature space. Using wavelet-based multi-resolution decomposition, two different sets of texture features are formulated for clustering. For each feature set, different distance measurement techniques are designed and experimented for clustering images in a database. The experimental results demonstrate that the retrieval efficiency and effectiveness improve when our clustering approach is used.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1009859912970
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