Content based annotation and retrieval in RAIDER

  • Authors:
  • Stephanie Fountain;Tieniu Tan

  • Affiliations:
  • Department of Computer Science, University of Reading, Reading, England;National Laboratory of Pattern Recognition, Institute of Automation, Beijing, China

  • Venue:
  • IRSG'98 Proceedings of the 20th Annual BCS-IRSG conference on Information Retrieval Research
  • Year:
  • 1998

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Abstract

A new system, RAIDER (Retrieval and Annotation of Image Databases), has been developed for the management of image databases. RAIDER was designed to combat the inadequacies and inefficiencies of traditional systems via a combination of content based retrieval and enhanced text based query capabilities. The interactive annotation technique employed in RAIDER is both quick and easy to use. As a whole RAIDER provides a flexible and efficient way to build and search image databases. A system overview is given in this paper together with details of the rotation invariant texture analysis techniques developed for use in its implementation. Two methods of texture analysis are presented; a multichannel filtering technique based on Gabor filtering and an edge attribute method which utilises the Sobel edge operator. Retrieval and classification experiments are performed on a database of 1320 images taken from 44 Brodatz classes. The two methods resistance to Gaussian noise are characterised via content based retrieval experiments based on similar image queries. Finally an object selection tool (used during annotation) based on texture and colour analysis is presented. Experimental results are given throughout the paper where applicable.