scholarly journals IMAGE EDGE DETECTION USING YUV COLOR SPACE: AN ALTERNATIVE TO RGB COLOR SPACE

2015 ◽  
pp. 36-47
Author(s):  
Aliyu Musa ◽  
Sani Muhammad ◽  
Abubakar Muhammad ◽  
Abubakar Umar ◽  
Khadija Sani ◽  
...  
Keyword(s):  
Edge Detection ◽  
Color Space ◽  
Image Edge Detection ◽  
Image Edge ◽  
Rgb Color Space

An Improved Approach of Color Edge Detection Based on Robustness of Cell Neural Network

2011 ◽  
Vol 403-408 ◽  
pp. 1879-1882
Author(s):  
Qing Ling Jiang
Keyword(s):  
Neural Network ◽  
Edge Detection ◽  
Color Image ◽  
Color Space ◽  
Robustness Analysis ◽  
Detection Algorithm ◽  
Edge Extraction ◽  
Image Edge Detection ◽  
Image Edge ◽  
Rgb Color Space

For the disadvantage of cell neural network (CNN) method which can not directly deal with color images, we present a new color image edge detection algorithm according to CNN model. Through robustness analysis for CNN template, a CNN theorem be carried out which can compute in the RGB color space. The experimental results show that our approach can effectively carry out edge extraction and locates accurately.

A Novel Edge Detection Algorithm of Color Image

2013 ◽  
Vol 446-447 ◽  
pp. 976-980
Author(s):  
De Rui Song ◽  
Dao Yan Xu ◽  
Li Li
Keyword(s):  
Edge Detection ◽  
Impulse Noise ◽  
Color Image ◽  
Peer Group ◽  
Color Space ◽  
Noise Removal ◽  
Detection Algorithm ◽  
Image Edge Detection ◽  
Image Edge ◽  
Image Edges

This paper proposes a novel algorithm of edge detection using LUV color space. Firstly, according to peer group filtering (PGF), a nonlinear algorithm for image smoothing and impulse noise removal in color image is used. Secondly, color image edges in an image are obtained automatically by combining an improved isotropic edge detector and a fast entropy threshold technique. Thirdly, according to color distance between the pixel and its eight neighbor-pixels, color image edges can further be detected. Finally, the experiment demonstrates the outcome of proposed algorithm in color image edge detection.

scholarly journals Enhancing Ant-Based Algorithms for Medical Image Edge Detection by Admissible Perturbations of Demicontractive Mappings

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 885
Author(s):  
Vasile Berinde ◽  
Cristina Ţicală
Keyword(s):  
Edge Detection ◽  
Medical Image ◽  
Test Functions ◽  
Head Ct ◽  
X Ray ◽  
Numerical Tests ◽  
Image Edge Detection ◽  
Evaluation Of Parameters ◽  
Image Edge ◽  
Demicontractive Mappings

The aim of this paper is to show analytically and empirically how ant-based algorithms for medical image edge detection can be enhanced by using an admissible perturbation of demicontractive operators. We thus complement the results reported in a recent paper by the second author and her collaborators, where they used admissible perturbations of demicontractive mappings as test functions. To illustrate this fact, we first consider some typical properties of demicontractive mappings and of their admissible perturbations and then present some appropriate numerical tests to illustrate the improvement brought by the admissible perturbations of demicontractive mappings when they are taken as test functions in ant-based algorithms for medical image edge detection. The edge detection process reported in our study considers both symmetric (Head CT and Brain CT) and asymmetric (Hand X-ray) medical images. The performance of the algorithm was tested visually with various images and empirically with evaluation of parameters.

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