AN OVERVIEW OF CONTENT-BASED IMAGE RETRIEVAL

Content based image retrieval (CBIR) depends on several factors, such as, feature extraction method (the usage of appropriate features in CBIR), similarity measurement method and mathematical transform (chosen to calculate effective features), feedback usage and etc. All these factors are important in CBIR to enhance image retrieval accuracy and effort. An efficient retrieval mechanism can be achieved by improving some of its influencing factors. For this purpose, this paper provides a brief review of the factors that have an impact (positive or negative) on the CBIR. The usage of low-level image features such as shape, texture and color are assembling information from an image for recuperation. In this paper, various spectral methods of texture features extraction are discussed. In addition, all the current methods of demonstrating image texture features in the modern literature have been investigated for the purpose to achieve the research’s aim (to discover the most adequate features in CBIR that support image retrieval quality and retrieve the relevant images to the query image ). This paper also addresses the shortcomings of one spectral approach and the solutions provided by another approach for finding the most effective approach in texture feature representation.

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