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2006
Springer

A multi-step strategy for approximate similarity search in image databases

9 years 10 months ago
A multi-step strategy for approximate similarity search in image databases
Many strategies for similarity search in image databases assume a metric and quadratic form-based similarity model where an optimal lower bounding distance function exists for filtering. These strategies are mainly two-step, with the initial "filter" step based on a spatial or metric access method followed by a "refine" step employing expensive computation. Recent research on robust matching methods for computer vision has discovered that similarity models behind human visual judgment are inherently non-metric. When applying such models to similarity search in image databases, one has to address the problem of non-metric distance functions that might not have an optimal lower bound for filtering. Here, we propose a novel three-step "prune-filter-refine" strategy for approximate similarity search on these models. First, the "prune" step adopts a spatial access method to roughly eliminate improbable matches via an adjustable distance threshold. Se...
Paul Wing Hing Kwan, Junbin Gao
Added 13 Jun 2010
Updated 13 Jun 2010
Type Conference
Year 2006
Where ADC
Authors Paul Wing Hing Kwan, Junbin Gao
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