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A Fuzzy Set Approach for Edge Detection
Pushpajit A.Khaire, Dr. Nileshsingh V. Thakur
Pages - 403 - 412     |    Revised - 15-11-2012     |    Published - 31-12-2012
Volume - 6   Issue - 6    |    Publication Date - December 2012  Table of Contents
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KEYWORDS
Edge Detection, Fuzzy Set, BSD (Berkeley Segmentation Database), Ground Truth, PSNR
ABSTRACT
Image segmentation is one of the most studied problems in image analysis, computer vision, pattern recognition etc. Edge detection is a discontinuity based approach used for image segmentation. In this paper, an edge detection using fuzzy set is proposed, where an image is considered as a fuzzy set and pixels are taken as elements of fuzzy set. The fuzzy approach converts the color image to a partially segmented image; finally an edge detector is convolved over the partially segmented image to obtain an edged image. The approach is implemented using MATLAB 7.11. (R2010b). For qualitative and quantitative comparison, BSD (Berkeley Segmentation Database) images are used for experimentation. Performance parameters used are PSNR (dB) and Performance ratio (PR) of true to false edges. It has been shown that the proposed approach performs better than Canny’s edge detection algorithm under almost all scenarios. The proposed approach reduces false edge detection and double edges.
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Mr. Pushpajit A.Khaire
RCOEM - India
pushpjitkhaire@gmail.com
Dr. Dr. Nileshsingh V. Thakur
- India