Application of the fuzzy logic in content-based image retrieval

This paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image features, not the features themselves; secondly making use of the fuzzy inference to instruct the weights assignment among various image features; thirdly expressing the subjectivity of human perceptions by fuzzy rules impliedly; lastly we propose an improvement on the traditional histogram called the Average Area Histogram (AAH) to represent color features. Experimentally we realized a fuzzy logic-based image retrieval system with good retrieval performance.Facultad de Informátic

Content Based Image Retrieval with Fuzzy Geometrical Features

Abstract — This paper presents a robust technique for Content Based Image Retrieval (CBIR) using fuzzy edge map of an image. Fuzzy compactness vector is computed from fuzzy edge map thresholded at different levels of the unsegmented image, which also incorporates gray level contrast information embedded in the edges. The resemblance of two images is defined as the similarity between the computed feature vectors. I