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.

Application of Petrochemical Heat Equipments' State Inspection Based on Threshold Value of Infrared Image Segmentation

2013 ◽  
Vol 712-715 ◽  
pp. 1947-1951
Author(s):  
Lin Lin Cui ◽  
Hua Lai ◽  
Yong Wang Tang ◽  
Qiang Cao
Keyword(s):  
Image Segmentation ◽  
Fault Diagnosis ◽  
Infrared Image ◽  
Threshold Value ◽  
State Inspection ◽  
Experimental Results ◽  
Optimal Threshold ◽  
Target Area ◽  
The Relationship ◽  
Infrared Image Segmentation

According to the problem of petrochemical heat equipment status inspection and fault diagnosis, a method based on threshold value of infrared image segmentation was presented. Studying the infrared image segmentation based on threshold value we can get the relationship between threshold value and the target area, threshold value and the temperature. Categories of differential variance method and optimal threshold value method of the experimental results were compared, and feasibility of this method was verified.

The Research of Furnace Temperature Control on Thermocouple Auto-Calibration System

2014 ◽  
Vol 494-495 ◽  
pp. 1114-1117
Author(s):  
Tuo Li ◽  
Hua Lai ◽  
Lin Lin Cui
Keyword(s):  
Image Segmentation ◽  
Fault Diagnosis ◽  
Temperature Control ◽  
Infrared Image ◽  
Threshold Value ◽  
Target Area ◽  
Calibration System ◽  
Furnace Temperature ◽  
The Relationship ◽  
Infrared Image Segmentation

According to the problem of petrochemical heat equipment status inspection and fault diagnosis, a method based on threshold value of infrared image segmentation was presented. Studying the infrared image segmentation based on threshold value we can get the relationship between threshold value and the target area, threshold value and the temperature. Categories of differential variance method and optimal threshold value method of the experimental results were compared, and feasibility of this method was verified.

Guide filter-based gradient vector flow module for infrared image segmentation

2015 ◽  
Vol 54 (33) ◽  
pp. 9809 ◽  
Author(s):  
Fan Zhao ◽  
Jian Zhao ◽  
Wenda Zhao ◽  
Feng Qu
Keyword(s):  
Image Segmentation ◽  
Infrared Image ◽  
Gradient Vector Flow ◽  
Gradient Vector ◽  
Infrared Image Segmentation

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.

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