Fuzzy Inference System Applied to Edge Detection in Digital Images

2016 ◽  
Author(s):  
Cristiano Jacques Miosso ◽  
Adolfo Bauchspiess
Keyword(s):  
Edge Detection ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Digital Images ◽  
Inference System

Edge Detection Based on a Fuzzy Inference System

2011 ◽  
Vol 121-126 ◽  
pp. 4436-4440
Author(s):  
Shu Liang Sun ◽  
Cheng Lian Liu ◽  
Si Sheng Chen
Keyword(s):  
Edge Detection ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Linear Filter ◽  
High Contrast ◽  
Contrast Variation ◽  
Good Effort ◽  
Inference System ◽  
First Order ◽  
Sobel Operator

First-order linear filter is a wide application algorithm to detect edge in digital image. However it dosen’t make good effort to the image where contrast varies much, or luminance takes on non-uniform. In this paper, a fuzzy inference system (FIS) is made up and used to detect edges. The experiment shows that FIS is much better in edge detection when the image with high contrast variation than with the linear Sobel operator. The FIS is also more precise in edge detection than Sobel operator.

scholarly journals Edge Detection Fuzzy Inference System

2013 ◽  
Vol 4 (1) ◽  
pp. 148-155 ◽  
Author(s):  
Er. Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Fuzzy Logic ◽  
Edge Detection ◽  
Fuzzy Inference System ◽  
Abrupt Change ◽  
Fuzzy Inference ◽  
Horizontal Line ◽  
Inference System ◽  
Edge Operator ◽  
Vertical Location ◽  
Canny Edge

In this paper a method has been developed for automatic edge detection of an digital image. An edge is made up of those pixels at which there is an abrupt change in the intensity. These pixels are known as edge pixels and are connected to give an edge. In this paper we have developed a mamdanis fuzzy inference system in MATLAB 2008 using fuzzy logic tool box. A smallest possible 2X2 window is used as a scanning mask. Mask slides over the whole image pixel by pixel, first horizontally in topmost horizontal line then after reaching at the end of line, it increments to check the next vertical location and it continues till the whole image is scanned. The FIS built has 4 inputs, each input representing a pixel for 2X2 mask, and 1 output that represents pixel under consideration. The rule editor consists of sixteen fuzzy rules. The results thus obtained are compared with Sobel edge operator and Canny edge operator.

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