Novel approaches are needed to support content-based retrieval on
large-scale geographic image 数据挖掘研究院
databases. In this paper, we present a new approach termed Keyblock
for content-based geographic
image retrieval, which is a generalization of the text-based
information retrieval technology in the image 数据挖掘实验室
domain. In this approach, methods for extracting comprehensive
geographic image features are provided,
which are based on the frequency and correlation of representative
blocks, termed keyblocks, of the
geographic image database. Keyblocks, which are analogous to index
terms in text document retrieval, 数据挖掘研究院
can be constructed by exploiting various clustering algorithms. By
comparing the performance of our 数据挖掘研究院
approach with conventional techniques using color feature and wavelet
texture feature, the experimental
results demonstrate the effectiveness of our approach for geographic
image retrieval.
