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Author Country (or Countries)

China

Abstract

By the virtue of BOF to describe high-dimensional data, in this article, we propose an effective retrieval strategy employing multi-resolution BOF to accelerate the match. The main idea is to improve the overall retrieval efficiency of BOF Descriptive Vector via the construction of BOF Low-resolution Vector and the comparison under low resolution to filter high-resolution candidate vectors. Based on stratified construction, we have improved uniform quantization multi-resolution BOF and proposed a non-linear Non-uniform quantization multi-resolution BOF method, which is combined with VA-file. At last, K-nearest neighbor retrieval algorithm is given. Experiments prove that this method has effectively increased the retrieval efficiency, improved the I/O function when loading mass image datasets and raised the system efficiency.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.12785/amis/090152

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