Abstract: An image retrieval system contains a database with a large number of images. The system retrieves images from the database that are similar to a query image entered by the user. The images in the database are grouped in clusters according to a similarity criterion so that mutually similar images reside in the same cluster. Each cluster has a cluster center which is representative for the images in it. A first step of the search to similar images selects the clusters that may contain images similar with the query image, by comparing the query image with the cluster centers of all clusters. A second step of the search compares the images in the selected clusters with the query image in order to determine their similarity with the query image.

Abstract: An image retrieval system contains a database with a large number of images. The system retrieves images from the database that are similar to a query image entered by the user. The images in the database are grouped in clusters according to a similarity criterion so that mutually similar images reside in the same cluster. Each cluster has a cluster center which is representative for the images in it. A first step of the search to similar images selects the clusters that may contain images similar with the query image, by comparing the query image with the cluster centers of all clusters. A second step of the search compares the images in the selected clusters with the query image in order to determine their similarity with the query image.

Abstract: An image retrieval system contains a database with a large number of images. The system retrieves images from the database that are similar to a query image entered by the user. The images in the database are grouped in clusters according to a similarity criterion so that mutually similar images reside in the same cluster. Each cluster has a cluster center which is representative for the images in it. A first step of the search to similar images selects the clusters that may contain images similar with the query image, by comparing the query image with the cluster centers of all clusters. A second step of the search compares the images in the selected clusters with the query image in order to determine their similarity with the query image.

Abstract: In an image retrieval system, a database with a large number of images is searched to find one or more images meeting the specification of a user. This specification is given in the form of a query image. The system determines the similarity between the query image and a particular image from the database by comparing the color histograms of the two images. The histograms are treated as statistical distributions and the similarity is determined on the basis of an information theoretic measure of the distributions. In a first embodiment, the similarity is determined using the Kullback informational divergence of the two histograms. In a second embodiment, the similarity is based on the entropy of the distribution of similarity coefficients of the two histograms is used.