Handling Sub-Image Queries in Content-Based Retrieval of High Resolution Art Images
Stephen Chan , University of Southampton, United Kingdom
Paul Lewis , University of Southampton, United Kingdom
Kirk Martinez , University of Southampton, United Kingdom
James Stevenson , Victoria & Albert Museum, United Kingdom
Christian Lahanier , Laboratoire de recherche des musées de France, France

Short Paper: Short Paper 6: Looking for Content

The paper describes work which is part of the Artiste project to develop a distributed database of Art Images from four major European art galleries. One aspect of the project involves the development of content-based retrieval and navigation facilities and a particular objective is to provide a facility for retrieving an image from the collection or navigating to related information in the database, given a query image which may be only a part of a particular image in the collection. The query sub-image may be a poor quality reproduction of part of the original and may be digitised under significantly different conditions. The paper outlines one of the recent approaches we have developed to facilitate such modes of retrieval and navigation. It is based on the use of colour coherence vectors extracted from image patches for the query and target images at a range of scales with multiple vector matching in order to find the best sub-image matches. Some results of the application of the technique are described and its success at sub-image location from a collection of images, including many at very high resolution, is demonstrated.


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Published: 01/09/01
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