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Robust image retrieval using bag of visual words with fuzzy codebooks and fuzzy assignment

Content-based retrieval systems leverage low level features such as color, texture or local information of images to find similar images to a respective query image. In recent years the Bag of Visual Words (BoVW) approach, which relies on quantized visual information around local image patches, has gained importance in image retrieval. In this paper we focus on fuzzy algorithms, in order to improve the descriptiveness of image descriptors. We extend the BoVW approach by applying fuzzy clustering and fuzzy assignment to take a step towards more effective visual descriptors, which are matched against each other in content-based similarity searches.