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.
Cite
CITATION STYLE
Ho, K. H. L., & Ohnishi, N. (1997). FEDGE — Fuzzy edge detection by fuzzy categorization and classification of edges. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1188, pp. 182–196). Springer Verlag. https://doi.org/10.1007/3-540-62474-0_14
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