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On Fuzzy Labelled Image Segmentation Based on Perceptual Features

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

Abstract

One of the monolithic goals of Computer Vision (CV) is to automatically interpret general digital images of arbitrary scenes. Although this goal has produced a vast array of research, a solution to the general problem has not been found. The difficulty of this goal has caused the field to focus on smaller, more constrained problems related with the different tasks involved, such as: noise removal, smoothing, and sharpening of contrast -low-level-; segmentation of images to isolate objects and regions, and description and recognition of the segmented regions -intermediate-level-; and interpretation of the scene -high-level-.

Work partially supported by the Spanish CICYT Project TIC2002-02791.

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© 2004 Springer-Verlag Berlin Heidelberg

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Sobrevilla, P., Montseny, E. (2004). On Fuzzy Labelled Image Segmentation Based on Perceptual Features. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_116

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_116

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

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