A Self-Adaptive Edge Detection Approach by Improved Isotropic Sobel and OTSU

2013 ◽  
Vol 385-386 ◽  
pp. 1495-1499 ◽  
Author(s):  
Ji Peng Huang ◽  
Shuang Qiao
Keyword(s):  
Edge Detection ◽  
High Precision ◽  
Digital Image ◽  
Threshold Value ◽  
Simulation Experiments ◽  
Image Detection ◽  
Adaptive Approach ◽  
Detection Approach ◽  
Image Edge ◽  
Self Adaptive

This paper presents a self-adaptive approach to detect the edge of target in a digital image, and the proposed approach is based on eight-direction Isotropic Sobel and OTSU. Simulation experiments in matlab show that the approach can set the threshold value of an image automatically, has high precision in image detection, good connectivity, the uniform image edge magnitude for all directions and suppresses the noise well.

A WT-Based Edge Detection with Adaptive Threshold

2011 ◽  
Vol 204-210 ◽  
pp. 1386-1389
Author(s):  
Deng Yin Zhang ◽  
Li Xiao ◽  
Shun Rong Bo
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Value Iteration ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Image Edge ◽  
Threshold Setting

The existing edge detection algorithms with wavelet transform need to artificially set the threshold value and are lack of flexibility.To salve the limitations, in this paper, we propose a WT(wavelet transform)-based edge detection algorithm with adaptive threshold, which uses threshold value iteration method to achieve adaptive threshold setting. Comparison of experiment results for the CT image shows that the method which improve the clarity and continuity of the image edge can effectively distinguish edge and noise, and get more completely information of the edge. It has good application value in the fields of medical clinical diagnosis and image processing.

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.

Application of Petrochemical Heat Equipments' State Inspection Based on the Edge Detection of Infrared Image Segmentation

2013 ◽  
Vol 303-306 ◽  
pp. 970-974
Author(s):  
Lin Lin Cui ◽  
Hua Lai ◽  
Yong Wang Tang ◽  
Ming Jie Qi
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Infrared Image ◽  
Threshold Value ◽  
State Inspection ◽  
Experimental Result ◽  
Target Area ◽  
Image Edge ◽  
Roberts Operator ◽  
Infrared Image Segmentation

According to the problem of petrochemical heat equipment status inspection and fault diagnosis, a method based on edge detection of infrared image segmentation was presented studying the infrared image segmentation based on edge detection and combining Roberts operator into best threshold segmentation method to do simulation of buoyant, medium and heavy damaged equipments. Experimental result shows that edge detection operator of best threshold value has ideal effects to the image edge extraction's target area of thermal infrared equipment.

scholarly journals Algorithmic Approaches For Image Edge Detection

2021 ◽  
Vol 10 (3) ◽  
pp. 1942-1948
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Edge Detection ◽  
Image Edge ◽  
Algorithmic Approaches

Edge detection is most important technique in digital image processing. It play an important role in image segmentation and many other applications. Edge detection providesfoundation to many medical and military applications.It difficult to generate a generic code for edge detection so many kinds ofalgorithms are available. In this article 4 different approaches Global image enhancement with addition (GIEA), Global image enhancement with Multiplication (GIEM),Without Global image enhancement with Addition (WOGIEA),and without Global image enhancement with Multiplication (WOGIEM)for edge detection is proposed. These algorithms are validatedon 9 different images. The results showthat GIEA give us more accurate results as compare to other techniques.

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