Automatic and Semi-Automatic Techniques for Image Annotation

Automatic and Semi-Automatic Techniques for Image Annotation

Biren Shah (University of Louisiana at Lafayette, USA), Ryan Benton (University of Louisiana at Lafayette, USA), Zonghuan Wu (University of Louisiana at Lafayette, USA) and Vijay Raghavan (University of Louisiana at Lafayette, USA)
Copyright: © 2007 |Pages: 23
DOI: 10.4018/978-1-59904-370-8.ch006

Abstract

When retrieving images, users may find it easier to express the desired semantic content with keywords than visual features. Accurate keyword retrieval can only occur when images are completely and accurately described. This can be achieved either through laborious manual effort or automated approaches. Current methods for automatically extracting semantic information from images can be classified into (a) text-based methods, which use metadata such as ontological descriptions and/or text associated with images, to assign and/or refine annotations, and (b) image-based methods, which focus on extracting semantic information directly from image content. The focus of this chapter is to create an awareness and understanding of research and advances in this field, by introducing them to basic concepts and theories and then by classifying, summarizing, and describing works from the published literature. It will also identify unsolved problems and offer suggestions for future research directions.

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