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Gowri Jeyaraman
Bharathiar University

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An Edge Exposure using Caliber Fuzzy C-means With Canny Algorithm Gowri Jeyaraman; Janakiraman Subbiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp59-68

Abstract

Edge exposure or edge detection is an important and classical study of the medical field and computer vision.  Caliber Fuzzy C-means (CFCM) clustering Algorithm for edge detection depends on the selection of initial cluster center value. This endeavor to put in order a collection of pixels into a cluster, such that a pixel within the cluster must be more comparable to every other pixel. Using CFCM techniques first cluster the BSDS image, next the clustered image is given as an input to the basic canny edge detection algorithm. The application of new parameters with fewer operations for CFCM is fruitful. According to the calculation, a result acquired by using CFCM clustering function divides the image into four clusters in common. The proposed method is evidently robust into the modification of fuzzy c-means and canny algorithm. The convergence of this algorithm is very speedy compare to the entire edge detection algorithms. The consequences of this proposed algorithm make enhanced edge detection and better result than any other traditional image edge detection techniques.
Co-Authors Janakiraman Subbiah