A SIMILARITY METRIC IN IMAGE SEARCHING

Abstract

Similarity metric is a key component in query-by-example image searching with visual features. After extraction of image visual features, the scheme of computing their similarities can affect the system performance dramatically — the image searching results are normally displayed in decreasing order of similarity (alternatively, increasing order of distance) on the graphical interface for end users. Unfortunately, conventional similarity metrics, in image searching with visual features, usually encounter several difficulties, namely, lighting, background, and viewpoint problems. From the signal processing point of view, this paper introduces a novel similarity metric and therefore reduces the above three problems to some extent. The effectiveness of this newly developed similarity metric is demonstrated by a set of experiments upon a small image ground truth.