This paper presents image processing algorithms designed to analyse the colour CIE Lab histogram of high resolution
images of paintings. Three algorithms are illustrated which attempt to identify colour clusters, cluster shapes due to
shading and finally to identify pigments. Using the image collection and pigment list of the National Gallery London
large numbers of images within a restricted period have been classified with a variety of algorithms. The image
descriptors produced were also used with suitable comparison metrics to obtain content-based retrieval of the images.
The growing number of large multimedia collections has led to an increased interest in content-based retrieval research. Applications of content-based techniques to image retrieval is an active research area but much less work has been reported on content-based retrieval of 3-D objects in a multimedia database context. Increasingly such objects are being captured and added to multimedia collections and the European project, SCULPTEUR, is developing a museum information system which includes the introduction of facilities for content-based retrieval of the 3-D representations.
This paper provides a comparison and evaluation of a range of 3-D shape descriptors and distance metrics which have been introduced into the SCULPTEUR project to demonstrate their use for content-based retrieval applications. Results show that while particular descriptors and distance metrics provide good overall performance, it can be more appropriate to choose different descriptors for different search tasks.