A survey on image retrieval performance of different bag of visual words indexing techniques

In this paper a survey has been carried out over image retrieval performances of bag of visual words (BoVW) method using different indexing techniques. Bag of visual word method is a content based image retrieval technique, where images are represented as a sparse vector of occurrences of visual words. In this paper different indexing techniques are used to compute near similar visual word vectors of a query image. Locality sensitive hashing, SR-tree based indexing and naive L
₁
and L
₂
norm based distance metric calculation are used here. Standard datasets like, UKBench [19], holiday dataset [9] and images from SMARAK
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are used for performance analysis.