A Study on Implementation of Edge Detection Algorithms Based on Fuzzy Membership Models


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 5, No. 9, pp. 2447-2456, Sep. 1998
10.3745/KIPSTE.1998.5.9.2447,   PDF Download:

Abstract

Edge detection in the presence of noise is a well-known problem. This paper attempts to implement edge detection algorithms using fuzzy reasoning of fuzzy membership models. It examines an application motived approach for solving the problem. Our approach is divided into three stages: filtering, segmentation and tracing. Filtering removes the noise from the original image and segmentation determines the edges and detects them. Finally, tracing assembles the edges into the related structure. Proposed method can be used effectively on these procedures by using fuzzy reasoning based on fuzzy models. It is compared with the previous edge detection algorithms with favorable results. Simulation results of the research are presented and discussed.


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Cite this article
[IEEE Style]
L. B. Ho, K. S. Yeon, K. K. Hee, "A Study on Implementation of Edge Detection Algorithms Based on Fuzzy Membership Models," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 5, no. 9, pp. 2447-2456, 1998. DOI: 10.3745/KIPSTE.1998.5.9.2447.

[ACM Style]
Lee Bae Ho, Kim So Yeon, and Kim Kwang Hee. 1998. A Study on Implementation of Edge Detection Algorithms Based on Fuzzy Membership Models. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 5, 9, (1998), 2447-2456. DOI: 10.3745/KIPSTE.1998.5.9.2447.