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Computer Vision and Decision Support

  • Chapter
The Perception of Visual Information

Abstract

The preceding chapters describe basic mechanisms by which visual information is detected by the eye and brain, as well as fundamental principles of perception including texture and object recogniton and cognitive processing. In addition, Chaps. 7 and 8 discuss computer processing techniques that may make specific image features easier to perceive. In this chapter, we consider ways that computers can directly extract features from images (computer vision). and understand their meaning and support human cognition (decision support). For example, in medical imaging, computer-vision techniques may be used to detect and characterize a possible abnormality (such as a tumor mass) in an image of the breast and then artificial intelligence (AI) techniques may be employed to merge the extracted features into a diagnostic decision regarding the possibility of malignancy. Computer processing techniques include image processing, image segmentation, and feature extraction. Decision support tools include rule-based expert systems, discriminant analysis,, Bayesian methods, and neural networks among others.

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Authors
  1. Henry A. Swett
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  2. Maryellen L. Giger
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  3. Kunio Doi
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Editors and Affiliations

  1. Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA

    William R. Hendee

  2. Bristol General Hospital, Guinea Street, Bristol, B51 65Y, UK

    Peter N. T. Wells

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Swett, H.A., Giger, M.L., Doi, K. (1997). Computer Vision and Decision Support. In: Hendee, W.R., Wells, P.N.T. (eds) The Perception of Visual Information. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1836-4_10

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  • DOI: https://doi.org/10.1007/978-1-4612-1836-4_10

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