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Fuzzy Set Methods in Computer Vision

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An Introduction to Fuzzy Logic Applications in Intelligent Systems

Part of the book series: The Springer International Series in Engineering and Computer Science ((SECS,volume 165))

Abstract

Computer vision is the study of theories and algorithms involving the sensing and transmission of images; preprocessing of digital images for noise removal, smoothing, or sharpening of contrast; segmentation of images to isolate objects and regions; description and recognition of the segmented regions; and finally interpretation of the scene. We normally think of images in the visible spectrum, either monochrome or color, but in fact, images can be produced by a wide range of sensing modalities including X-rays, neutrons, ultrasound, pressure sensing, laser range finding, infrared, and ultraviolet, to name a few.

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Author information

Authors and Affiliations

  1. Electrical and Computer Engineering, University of Missouri-Columbia, Columbia, Missouri, 65211, USA

    James M. Keller & Raghu Krishnapuram

Authors
  1. James M. Keller
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  2. Raghu Krishnapuram
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Editor information

Editors and Affiliations

  1. Iona College, USA

    Ronald R. Yager

  2. University of California, Berkeley, USA

    Lotfi A. Zadeh

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© 1992 Springer Science+Business Media New York

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Keller, J.M., Krishnapuram, R. (1992). Fuzzy Set Methods in Computer Vision. In: Yager, R.R., Zadeh, L.A. (eds) An Introduction to Fuzzy Logic Applications in Intelligent Systems. The Springer International Series in Engineering and Computer Science, vol 165. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3640-6_6

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  • DOI: https://doi.org/10.1007/978-1-4615-3640-6_6

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6619-5

  • Online ISBN: 978-1-4615-3640-6

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