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2008
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Optimization of Content-Based Image Retrieval Functions

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Optimization of Content-Based Image Retrieval Functions
Feature extraction and similarity measurement are two important operations in content-based image retrieval systems. We optimize and vectorize typical feature extraction algorithms, mean and standard deviation, and some similarity measurement functions such as the Sum-of-Squared-Differences (SSD), the Sum-of-Absolute Differences (SAD), and histogram intersection on a general-purpose processor enhanced with SIMD extensions. In the straightforward implementation of the mean and standard deviation, there are two passes, one to compute the mean and one to compute the standard deviation. We use a single-loop approach that computes both the mean and the standard deviation in a single pass.
Asadollah Shahbahrami, Ben H. H. Juurlink
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where ISM
Authors Asadollah Shahbahrami, Ben H. H. Juurlink
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