"Using Structure, Color and Texture for
 Content-based Image Retrieval"

Abstract: Images are an essential component of modern data systems. In critical applications ranging from surveillance to medicine, efficient query systems are needed to quickly locate images with particular properties within large collections. Content-based image retrieval systems analyze image features to identify image content. Color and texture are two of the features traditionally used to approach this challenging problem.

At The University of Texas at Austin, we have found structure, derived by perceptual grouping, to be a valuable tool in our quest for better content-based image retrieval. Structure adds significantly to the efficiency of the image retrieval. This presentation focuses on deriving structure via perceptual grouping, and its use in image classification and retrieval. This use of structure does not entail the segmentation of the image. Our analysis shows that structure, color and texture form an excellent feature set for image retrieval. A hands-on comparison of results using color, texture and structure to retrieve images containing both natural and manmade objects will be demonstrated. Our system, which is available on the web, incorporates relevance feedback from the user to further refine the search. Future uses of our system in surveillance and video summarization will also be discussed.

Biography: J. K. Aggarwal has served on the faculty of The University of Texas at Austin College of Engineering since 1964 and is currently the Cullen Professor of Electrical and Computer Engineering and Director of the Computer and Vision Research Center. His research interests include computer vision and pattern recognition. A Fellow of IEEE since 1976 and IAPR since 1998, he received the Senior Research Award of the American Society of Engineering Education in 1992, and the 1996 Technical Achievement Award of the IEEE Computer Society. He has served as Chairman of the IEEE Computer Society Technical Committee on Pattern Analysis and Machine Intelligence (1987-1989); Director of the NATO Advanced Research Workshop on Multisensor Fusion for Computer Vision, Grenoble, France (1989); Chairman of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1993), and President of the International Association for Pattern Recognition (1992-94). He is a Life Fellow of IEEE and Golden Core member of IEEE Computer Society. He has authored and edited a number of books, chapters, proceedings of conferences, and papers.