Image edge extraction based on fuzzy theory and Sobel operator

2016 ◽  
Author(s):  
Yulan Liu ◽  
Yi Long
Keyword(s):  
Fuzzy Theory ◽  
Edge Extraction ◽  
Sobel Operator ◽  
Image Edge

Quantum image edge extraction based on classical Sobel operator for NEQR

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Ping Fan ◽  
Ri-Gui Zhou ◽  
Wenwen Hu ◽  
Naihuan Jing
Keyword(s):  
Edge Extraction ◽  
Quantum Image ◽  
Sobel Operator ◽  
Image Edge

Design of an image edge detection filter using the Sobel operator

10.1109/4.996 ◽  
1988 ◽  
Vol 23 (2) ◽  
pp. 358-367 ◽  
Author(s):  
N. Kanopoulos ◽  
N. Vasanthavada ◽  
R.L. Baker
Keyword(s):  
Edge Detection ◽  
Sobel Operator ◽  
Image Edge Detection ◽  
Image Edge ◽  
Detection Filter

Image Edge Extraction Based on SUSAN Operator

2014 ◽  
Vol 687-691 ◽  
pp. 3765-3768
Author(s):  
Nan Wang
Keyword(s):  
Edge Detection ◽  
High Precision ◽  
Extraction Method ◽  
The Other ◽  
Differential Detection ◽  
Edge Extraction ◽  
Image Edge ◽  
Circular Template

A new edge extraction method was put forward based on the SUSAN operator, according to the problems of poor anti-noise ability and edge detection incomplete of the conventional differential detection operator. The circular template and the center of the circle (template nuclear) were used in this method, the numbers of pixels was calculated through the comparison pixels value of template with the other points of pixels in the template circle, and then compared with the threshold, so as to the edge of images was extracted. The results showed that this method had high precision, and could be able to fully extract the edge of images. It is an effective method of extracting the edge of images.

scholarly journals Stochastic Fractal Search Algorithm for Template Matching with Lateral Inhibition

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Qifang Luo ◽  
Sen Zhang ◽  
Yongquan Zhou
Keyword(s):  
Lateral Inhibition ◽  
Template Matching ◽  
Search Algorithm ◽  
Inhibition Mechanism ◽  
Edge Extraction ◽  
Matching Problems ◽  
Matching Technique ◽  
Image Edge ◽  
Stochastic Fractal Search Algorithm ◽  
Stochastic Fractal Search

Template matching is a basic and crucial process for image processing. In this paper, a hybrid method of stochastic fractal search (SFS) and lateral inhibition (LI) is proposed to solve complicated template matching problems. The proposed template matching technique is called LI-SFS. SFS is a new metaheuristic algorithm inspired by random fractals. Furthermore, lateral inhibition mechanism has been verified to have good effects on image edge extraction and image enhancement. In this work, lateral inhibition is employed for image preprocessing. LI-SFS takes both the advantages of SFS and lateral inhibition which leads to better performance. Our simulation results show that LI-SFS is more effective and robust for this template matching mission than other algorithms based on LI.

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