scholarly journals Edge Detection Method Based on General Type-2 Fuzzy Logic Applied to Color Images

Information ◽  
2017 ◽  
Vol 8 (3) ◽  
pp. 104 ◽  
Author(s):  
◽  
◽  
Keyword(s):  
Fuzzy Logic ◽  
Edge Detection ◽  
General Type ◽  
Detection Method ◽  
Color Images ◽  
Edge Detection Method

An improved sobel edge detection method based on generalized type-2 fuzzy logic

2014 ◽  
Vol 20 (2) ◽  
pp. 773-784 ◽  
Author(s):  
Claudia I. Gonzalez ◽  
Patricia Melin ◽  
Juan R. Castro ◽  
Olivia Mendoza ◽  
Oscar Castillo
Keyword(s):  
Fuzzy Logic ◽  
Edge Detection ◽  
Detection Method ◽  
Sobel Edge Detection ◽  
Edge Detection Method ◽  
Generalized Type

Edge-Detection Method for Image Processing Based on Generalized Type-2 Fuzzy Logic

2014 ◽  
Vol 22 (6) ◽  
pp. 1515-1525 ◽  
Author(s):  
Patricia Melin ◽  
Claudia I. Gonzalez ◽  
Juan R. Castro ◽  
Olivia Mendoza ◽  
Oscar Castillo
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Edge Detection ◽  
Detection Method ◽  
Edge Detection Method ◽  
Generalized Type

Edge detection method based on Interval type-2 fuzzy systems for color images

2015 ◽  
Author(s):  
C. I. Gonzalez ◽  
J. R. Castro ◽  
O. Mendoza ◽  
A. Rodriguez-Diaz ◽  
P. Melin ◽  
...  
Keyword(s):  
Edge Detection ◽  
Fuzzy Systems ◽  
Detection Method ◽  
Color Images ◽  
Edge Detection Method ◽  
Interval Type

scholarly journals General Type-2 Fuzzy Sugeno Integral for Edge Detection

2019 ◽  
Vol 5 (8) ◽  
pp. 71
Author(s):  
Gabriela E. Martínez ◽  
Claudia I. Gonzalez ◽  
Olivia Mendoza ◽  
Patricia Melin
Keyword(s):  
Edge Detection ◽  
Figure Of Merit ◽  
General Type ◽  
Detection Method ◽  
General Process ◽  
Sugeno Integral ◽  
Morphological Gradient ◽  
Edge Detection Method ◽  
Image Gradients

A type-2 fuzzy edge detection method is presented in this paper. The general process consists of first obtaining the image gradients in the four directions—horizontal, vertical, and the two diagonals—and this technique is known as the morphological gradient. After that, the general type-2 fuzzy Sugeno integral (GT2 FSI) is used to integrate the four image gradients. In this second step, the GT2 FSI establishes criteria to determine at which level the obtained image gradient belongs to an edge during the process; this is calculated assigning different general type-2 fuzzy densities, and these fuzzy gradients are aggregated using the meet and join operators. The gradient integration using the GT2 FSI provides a methodology for achieving more robust edge detection, even more if we are working with blurry images. The experimental evaluations are performed on synthetic and real images, and the accuracy is quantified using Pratt’s Figure of Merit. The results values demonstrate that the proposed edge detection method outperforms other existing algorithms.

Edge Detection of Color Images Based on Improved Morphological Gradient Operators

2014 ◽  
Vol 511-512 ◽  
pp. 550-553 ◽  
Author(s):  
Jian Yong Liang
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Color Image ◽  
Color Images ◽  
Morphological Gradient ◽  
Image Edge Detection ◽  
Gradient Based ◽  
Image Edge ◽  
Edge Detection Method ◽  
Traditional Approaches

Edge detection is an old and hot topic in image processing, pattern recognition and computer vision. Numerous edge detection approaches have been proposed to gray images. It is difficult to extend these approaches to color image edge detection. A novel edge detection method based on mathematical morphology for color images is proposed in this paper. The proposed approach firstly compute vector gradient based on morphological gradient operators, and then compute the optimal gradient according to structure elements with different size. Finally, we use a threshold to binary the gradient images and then obtain the edge images. Experimental results show that the proposed approach has advantages of suppressing noise and preserving edge details and it is not sensitive to noise pixel. The finally edge images via the proposed method have high PSNR and NC compared with the traditional approaches.

scholarly journals Fuzzy Logic based Edge Detection Method for Image Processing

2018 ◽  
Vol 8 (3) ◽  
pp. 1863 ◽  
Author(s):  
Abdulrahman Moffaq Alawad ◽  
Farah Diyana Abdul Rahman ◽  
Othman O. Khalifa ◽  
Norun Abdul Malek
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Detection Method ◽  
Detection Task ◽  
Fuzzy Logic Method ◽  
Recognition Systems ◽  
Edge Detection Method ◽  
Depth Curves

Edge detection is the first step in image recognition systems in a digital image processing. An effective way to resolve many information from an image such depth, curves and its surface is by analyzing its edges, because that can elucidate these characteristic when color, texture, shade or light changes slightly. Thiscan lead to misconception image or vision as it based on faulty method. This work presentsa new fuzzy logic method with an implemention. The objective of this method is to improve the edge detection task. The results are comparable to similar techniques in particular for medical images because it does not take the uncertain part into its account.

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