Visual pattern weighting for near-duplicate image retrieval

Recently, there has been growing interest in mining co-location visual patterns from a collection of images. To find a proper usage of visual patterns in near-duplicate image retrieval systems, we study a TF-IDF weighting function for visual patterns. We show usage of TF and IDF respectively in this weighting function. Experiments demonstrate that 1) visual patterns and words should be weighted separately; 2) visual patterns consist of more frequent visual words would be more important; 3) visual patterns should be given lower weight values than visual words in near-duplicate image retrieval tasks.