Fuzzy models for color edge detection in impulse noise

2003 ◽  
Author(s):  
F. Russo ◽  
A. Lazzari
Keyword(s):  
Edge Detection ◽  
Impulse Noise ◽  
Fuzzy Models

scholarly journals A Novel Algorithm for Impulse Noise Removal and Edge Detection

2012 ◽  
Vol 38 (7) ◽  
pp. 30-34 ◽  
Author(s):  
Akansha Mehrotra ◽  
Krishna Kant Singh ◽  
M. J. Nigam
Keyword(s):  
Edge Detection ◽  
Impulse Noise ◽  
Noise Removal ◽  
Impulse Noise Removal ◽  
Novel Algorithm

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 Adaptive Edge Detection Method for Image Polluted by Hybrid Noise in Image Measurement

2011 ◽  
Vol 214 ◽  
pp. 156-162
Author(s):  
Bei Zhi Li ◽  
Hua Jiang Chen ◽  
Jian Guo Yang
Keyword(s):  
Edge Detection ◽  
Gaussian Noise ◽  
Impulse Noise ◽  
Detection Method ◽  
Selection Method ◽  
Threshold Selection ◽  
Hybrid Filter ◽  
Image Measurement ◽  
Canny Operator ◽  
Edge Detection Method

Edge detection directly affects the accuracy of image measurement. In this paper, focusing on the edge detection of the image of mechanical part polluted by hybrid noise consisting of Gaussian noise and impulse noise, an adaptive edge detection method is proposed. The proposed method combines a new hybrid filter smoothing noise adaptively with Canny operator to avoid the conflict of Canny operator between noise removing and edge locating, and uses Otsu threshold selection method to determine Dual-threshold of Canny operator adaptively. Using the gauge image polluted by hybrid noise as experiment object, the performance of the proposed method is evaluated qualitatively and quantitatively. Experimental results show that the proposed edge detection method has good performance.

Edge Detection of the Impulse Noise Pollution Image Based on the Rough Set

2013 ◽  
Vol 333-335 ◽  
pp. 904-907
Author(s):  
Qing Liu ◽  
Hong Bo Wei ◽  
Xiao Ping Yang
Keyword(s):  
Edge Detection ◽  
Set Theory ◽  
Rough Set ◽  
Impulse Noise ◽  
Rough Set Theory ◽  
Noise Pollution ◽  
Detection Algorithm ◽  
Target Area ◽  
Edge Detection Algorithm ◽  
Edge Features

The rough set is an effective tool to deal with incomplete, uncertain and fuzzy problem. In order to extract the edges information of the image by impulse noise pollution, further service for the follow-up image analysis and understanding, on the basis of the impulse noise pollution image preprocessing, an adaptive edge detection algorithm is put forward to process the impulse pollution image using rough set theory in this paper. Considering the target edge features can form a series of edge point constraints as the algorithm foundation,this method starts from the characteristics difference of the image edge and target area. Firstly, series edge constraint points are defined, and then the related questions of these conditions are solved by using rough set theory, so the edge detection algorithm is established. The experimental results show that this algorithm can effectively extract edge from the noise image information, to overcome the sensitivity of traditional algorithm for noise.

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