Analyse multirésolution pour la recherche et l'indexation d'images par le contenu dans les bases de données images - Application à la base d'images paléontologique Trans'Tyfipal
Recent content-based image retrieval systems offer an interactive visual browsing of images databases. These methods perform a classification of images (offline) into a search tree for users browsing (online). This approach shows three main problems:1) The size of decriptor vector (n>100) makes distance computing sensitive to dimensionality curse,2) Having many different kinds of attributes into descriptor vector does not help classification,3) In general, classification does not take in consideration users' search context. In this work, we propose a method based on building hierarchical signatures having small increasing sizes, this allows to take users' search context into consideration. …
Automatic building of a visual interface for content-based multiresolution retrieval of paleontology images
In this article we present research work in the field of content-based image retrieval in large databases applied to the paleontology image database of the Universite´ de Bourgogne, Dijon, France, called ‘‘TRANS’TYFIPAL.’’ Our indexing method is based on multiresolution decomposition of database images using wavelets. For each family of paleontology images we try to find a model image that represents it. The K-means automatic classification algorithm divides the space of parameters into several clusters. A model image for each cluster is computed from the wavelet transform of each image of the cluster. Then a search tree is built to offer users a graphic interface for retrieving images. So …