Color Image Edge Detection Arithmetic Based on Color Space

2012 ◽  
Author(s):  
Fengjing Zhang ◽  
Hong Cheng ◽  
Wenbang Sun ◽  
Yaoyu Zhang ◽  
Xiaojuan Wang
Keyword(s):  
Edge Detection ◽  
Color Image ◽  
Color Space ◽  
Image Edge Detection ◽  
Image Edge

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.

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.

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.

Fabric Image Edge Detection Based on Quaternion and Echo State Networks

2012 ◽  
Vol 263-266 ◽  
pp. 2483-2487
Author(s):  
Ang Yan Tu ◽  
Jian Cheng Chen
Keyword(s):  
Edge Detection ◽  
Color Image ◽  
Detection Algorithm ◽  
Good Effect ◽  
Vector Product ◽  
Edge Detection Algorithm ◽  
Echo State Networks ◽  
Image Edge Detection ◽  
Image Edge

Based on synthesizing quaternion and the R, G, B component of color image , a color image edge detection algorithm was proposed combining quaternion with Echo State Networks(ESN) in this paper . The pixel and its eight neighbourhood average is used to calculate vector product as the characteristic vectors of image edge. Then the ESN has been trained by the characteristic vectors. After training , the ESN is directly used for edge detection. Experiments show that this method has good effect of fabric edge detection, and have a stronger ability to keep the details.

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