Similarity queries in image databases

An object-oriented fuzzy data model for similarity detection in image databases

“…In order to support such retrieval, it is necessary to define a suitable similarity measure between the query image and the target image stored in the database. In the image database literature, several such similarity measures have been proposed for associative retrieval of images [3], [4], [5], [1]. However, adequate importance has not been given to the spatial and topological relations while defining such similarity measures.…”

Content Based Retrieval Systems in a Clinical Context

“…After all, when a user searches for something similar, he already has in mind his own concept of similarity, whose form is doubtlessly quite different from the metric spaces (such as the Euclidean) typically used for feature vector comparison. The similarity used by the CBIR systems should then be as similar as possible to the human concept of similarity if the results of the search are to be satisfactory [19]. Algorithmically modeling that behavior thus requires that the internal image representations closely reflect the ways in which users interpret, understand, and encode visual data.…”

Semantic modeling and knowledge representation in multimedia databases

“…Measures such as Minkowski distance [38], weighted distance [16], [37], color histogram intersection [41], and average distance [26], [34] can be used to evaluate the robustness of the mechanisms. The performance of a similarity-based search depends on the degree of imprecision and fuzziness introduced by the types of features used, and the computational characteristics of the search algorithm.…”