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Fuzzy Inference System based Edge Detection using Fuzzy Membership Functions
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 112 - Number 4 |
| Year of Publication: 2015 |
| Authors: E Boopathi Kumar, M Sundaresan |
10.5120/19654-1271
|
E Boopathi Kumar, M Sundaresan . Fuzzy Inference System based Edge Detection using Fuzzy Membership Functions. International Journal of Computer Applications. 112, 4 ( February 2015), 15-18. DOI=10.5120/19654-1271
Abstract
An edge is the boundary between an object and the background. It indicates the boundary between overlapping objects. Edge detection is one of the most commonly used operation analysis, which is used for enhancing and detecting edges in the image. In the literature review, there are many techniques developed to achieve the edge detection task such as Canny, Sobel, Prewitt, Roberts, Laplacian, Laplacian of Gaussian, Difference of Gaussian etc. This paper presents a fuzzy rule based algorithm, which is capable of detecting edges efficiently from the grayscale images. In this paper, Trapezoidal membership function is used to detect edges. Here, 3*3 masks are proposed and this method has provided better results than the other methods such as Triangular functions 2*2 and 3*3 masks.
References
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