Fuzzy histograms for efficient visual content representation: application to content-based image retrieval

Abstract

The efficiency of a content-based image retrieval (CBIR) system depends on the efficiency of the image visual content representation Usually, the extracted descriptors are organized in a binary framework, which, apart from the fact that it is sensitive to noise, it cannot also provide a physical interpretation of the image content. This problem is faced in this paper by introducing fuzzy histograms In particular, in the proposed scheme each image descriptor is allowed to belong to several (or all) classes but with a different degree of membership. Such a scheme removes possible noise existing in the extracted descriptors and simultaneously provides a physical interpretation of the image visual content. Experimental results are also presented, which explain the theoretical developments and illustrate the good performance of the proposed scheme to real-life image databases.