Cortina: a system for large-scale, content-based web image retrieval

ABSTRACT

Recent advances in processing and networking capabilities of computers have led to an accumulation of immense amounts of multimedia data such as images. One of the largest repositories for such data is the World Wide Web (WWW). We present Cortina, a large-scale image retrieval system for the WWW. It handles over 3 million images to date. The system retrieves images based on visual features and collateral text. We show that a search process which consists of an initial query-by-keyword or query-by-image and followed by relevance feedback on the visual appearance of the results is possible for large-scale data sets. We also show that it is superior to the pure text retrieval commonly used in large-scale systems. Semantic relationships in the data are explored and exploited by data mining, and multiple feature spaces are included in the search process.

REFERENCES

• 1: Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
• 2: Edgar Chávez , Gonzalo Navarro, A Probabilistic Spell for the Curse of Dimensionality, Revised Papers from the Third International Workshop on Algorithm Engineering and Experimentation, p.147-160, January 05-06, 2001
• 3: Richard O. Duda , Peter E. Hart , David G. Stork, Pattern Classification (2nd Edition), Wiley-Interscience, 2000
• 4: D. Heesch and S. Rüger. Performance boosting with three mouse clicks - relevance feedback for cbir. In 25th European Conference on Information Retrieval Research (ECIR, Pisa, Italy, 14-16 Apr 2003), pages pp 363--376, 2003.
• 5: B.S. Manjunath , Phillipe Salembier , Thomas Sikora, Introduction to MPEG-7: Multimedia Content Description Interface, John Wiley & Sons, Inc., New York, NY, 2002
• 6: L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.
• 7: M. F. Porter. An algorithm for suffix stripping. Program, 14(3):130--137, 1980.
• 8: K.-M. Wong and L.-M. Po. MPEG-7 dominant color descriptor based relevance feedback using merged palette histogram. In IEEE International Conference on Speech, Acoustics, and Signal Processing, 2004.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.m Miscellaneous

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services

General Terms:
Design, Documentation, Performance

Keywords:
MPEG-7, WWW, association rules, clustering, large-scale, online, relevance feedback, semantics, web image retrieval