Abstract
In this paper we will present a fuzzy edge detector, FEDGE. It is based on learning fuzzy edges by the method of Fuzzy Categorization and Classification (FCC). A set of images were used as examples for the definition of a fuzzy edge. FCC will try to recognize edges within a new image by collecting evidence from these examples. FEDGE demonstrates that FCC can be used homogeneously from pixel-level to symbolic level by recursively defining concepts using examples and classify a new image by collecting evidence from these examples. Result of FEDGE will also be given in this paper.
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© 1997 Springer-Verlag Berlin Heidelberg
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Ho, K.H.L., Ohnishi, N. (1997). FEDGE — Fuzzy edge detection by Fuzzy Categorization and Classification of edges. In: Martin, T.P., Ralescu, A.L. (eds) Fuzzy Logic in Artificial Intelligence Towards Intelligent Systems. FLAI 1995. Lecture Notes in Computer Science, vol 1188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62474-0_14
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DOI: https://doi.org/10.1007/3-540-62474-0_14
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