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In an automated search system, similarity is a key concept in solving a humantask. Indeed, human process is usually a natural categorization that underliesmany natural abilities such as image recovery, language comprehension, decisionmaking, or pattern recognition. In the image search axis, there are severalways to measure the similarity between images in an image database, to a queryimage. Image search by content is based on the similarity of the visualcharacteristics of the images. The distance function used to evaluate thesimilarity between images depends on the criteria of the search but also on therepresentation of the characteristics of the image; this is the main idea ofthe near and fuzzy sets approaches. In this article, we introduce a newcategory of beta type-2 fuzzy sets for the description of image characteristicsas well as the near sets approach for image recovery. Finally, we illustrateour work with examples of image recovery problems used in the real world.

Interval type-2 Beta Fuzzy Near set based approach to content based image retrieval