TUTORIAL
Gerald Schaefer (Loughborough University, UK)

Gerald Schaefer gained his BSc. in Computing from the University of Derby and his PhD in Computer Vision from the University of East Anglia. He worked at the Colour & Imaging Institute, University of Derby (1997-1999), in the School of Information Systems, University of East Anglia (2000-2001), in the School of Computing and Informatics at Nottingham Trent University (2001-2006), and in the School of Engineering and Applied Science at Aston University (2006-2009) before joining the Department of Computer Science at Loughborough University. His research interests are mainly in the areas of computational intelligence, medical imaging,colour image analysis, and the combination of these subject. He has published extensively in these areas with a total publication count exceeding 150. He is a member of the editorial board of 6 international journal, reviews for over 30 journals and serves on the programme committee of over 60 conferences. He is also the organiser of several international workshops and special sessions at conferences. His edited book on Computational Intelligence in Medical Imaging (CRC Press) will come out shortly, and several further edited books are due to be published in 2009 and 2010.

Tutorial Abstract:

Content-based image retrieval: techniques, challenges and recent developments

With the exponential growth of available digital imagery, effective and efficient techniques to manage these data are highly sought after. Clearly, image collections are only of use if they can be queried, yet manual annotation to enable such search is expensive, time consuming and error-prone. Luckily a lot of research in the last two decades has focussed on techniques to extract useful data directly from images to facilitate searching large image repositories. In this tutorial we will explain the underlying techniques, highlight some of the challenges to be overcome, and introduce some recent approaches that provide interesting and useful methods of working with image datasets.


Tutorial structure:

• Image databases and problems of manual annotation
• Content-based image retrieval by colour, texture, and shape
• Challenges: compression and colour variations
• Image classification
• Image annotation
• Image database visualisation and browsing