Image edge detection based on otsu and rough set theory

2011 ◽  
Author(s):  
Jing Zhang ◽  
Leilei Wang
Keyword(s):  
Edge Detection ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Image Edge Detection ◽  
Image Edge

A Novel Approach for Detectioning, Segmenting and Classifying Shadow Image Based on Rough Sets

2014 ◽  
Vol 513-517 ◽  
pp. 4175-4179
Author(s):  
Tie Min Chen ◽  
Hong Song He ◽  
Xin Cong Jiang
Keyword(s):  
Edge Detection ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Detection Algorithm ◽  
Shadow Image ◽  
Detection Algorithms ◽  
Image Edge Detection ◽  
Novel Approach ◽  
Image Edge

The disadvantages of domestic and oversea shadow image edge detection algorithms are analyzed. A novel shadow detection algorithm based on edge growing and rough set theory and subsequent solution is proposed. We describe how to detect image edge using condition attribution of rough set in this paper. Also, the method of thinning and connection for shadow edge using edge growing from the edge nodes is proposed. As can be seen from the experimental analysis, the method we proposed has better performance in edge detection and image segmentation.

Research on Road Surface Cracks Detection Based on Rough Set

2012 ◽  
Vol 566 ◽  
pp. 633-636 ◽  
Author(s):  
Wei Dong ◽  
Fang Fang Zhu ◽  
Zhong Dong Yin ◽  
Chan Zhang
Keyword(s):  
Edge Detection ◽  
Rough Set ◽  
Rough Sets ◽  
Road Surface ◽  
Surface Cracks ◽  
Horizontal Fracture ◽  
The Road ◽  
Image Edge Detection ◽  
Morphological Model ◽  
Image Edge

The road surface horizontal fracture, sink. Road image by filtering to remove noise, edge detection using several classical operators were analyzed, we propose a rough sets and fuzzy sets based on the morphological model, and apply it to the pavement crack image. By contrast to the other classic method, indicate that the method has successfully completed in the image edge detection.

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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