Table of Contents

1 Temperature Detection Methods Based on Machine Vision
1.1 Colorimetric thermometric model
1.1.1 Basic assumptions
1.1.2 The relationship of image grayscale and radiant temperature
1.1.3 Colorimetric temperature measurement model
1.2 Blackbody furnace calibration process
1.3 Image noise filtering method
1.3.1 Adaptive smooth filter denoising method
1.3.2 Adaptive median filter denoising method
1.3.3 Geometric mean filtering denoising method
1.3.4 Over-limit neighborhood filtering denoising method
1.3.5 Bilateral filter denoising method
1.3.6 Wavelet filter denoising method
1.4 Image edge detection method
1.4.1 Roberts operator
1.4.2 Sobel operator
1.4.3 Prewitt operator
1.4.4 Log operator
1.4.5 Canny operator
1.4.6 Morphological edge detection method
2 Temperature Detection in the Raceway Zone of Blast Furnace
2.1 Introduction
2.2 Theory and experiments
2.3 Methods to improve the temperature detection accuracy
2.3.1 Blackbody calibration for digital imaging system
2.3.2 Denoising for tuyere images
2.3.3 Edge detection for tuyere images
2.4 Combustion behavior and temperature in tuyere zone of BF
2.5 PCI process on the temperature variation in raceway zone of BF
2.5.1 Flame image temperature calculation
2.5.2 PCI rates
2.5.3 PCI cease processes
2.5.4 None PCI process
References
3 Uniformity and Activity of Blast Furnace Hearth
3.1 Introduction
3.2 Definitions of uniformity index and activity index
3.3 Experiments and temperature calculation
3.4 Uniformity index and activity index
3.4.1 Local uniformity index and local activity index
3.4.2 Ul and AI
References
4 Tuyere Coke Size and Temperature Distribution of BF
4.1 Introduction
4.2 Theory
4.2.1 Tuyere coke size detection
4.2.2 Temperature distribution calculation
4.3 Experiments
4.4 Results of tuyere coke size and temperature distribution
4.4.1 Calculation of tuyere coke size and temperature distribution of raceway zone
4.4.2 Results analyze
4.4.3 Calculation of coke belt length (CBL) in raceway zone of BF
References
5 Surface Temperature of Rail Steel Plates
5.1 Introduction
5.2 Emissivity calculation model
5.3 Theory
5.4 Experiments
5.4.1 Digital imaging system
5.4.2 Calibration for digital imaging system
5.4.3 Surface temperature variation during the rolling process
5.5 Temperature calculation results
5.5.1 Noise filtering results
5.5.2 Temperature detection results during rolling passes
References
6 Surface Defect Recognition of Aluminum Strips
6.1 Introduction
6.2 Aluminum strips images
6.3 NSST-KLPP model
6.4 Experiment and discussions
6.4.1 Experimental procedure
6.4.2 Experiment results
6.4.3 Comparison with common methods
6.4.4 Comparison of NSST,contourlet and DST
References
7 Surface Inspection of Continuous Casting Slabs
7.1 Introduction
7.2 Surface defects
7.3 DNST-GLCM-KSR model
7.4 Defect recognition algorithm
7.5 Defect recognition results
References
8 Surface Defect Recognition of Metals
8.1 Introduction
8.2 Construction of ICT
8.3 Defect recognition algorithms
8.4 Defect recognition results
References
9 Edge Detection of Retinal OCT Image
9.1 Introduction
9.2 Complex shearlet transform
9.3 Construction of detection formula
9.4 Numerical and visual experiments
9.5 Retinal OCT experiment
References
10 Detection of Character and Surface Defect in Steel Rail
10.1 Introduction
10.2 Experimental platform and experimental method
10.3 Methods
10.3.1 Photometric stereoscopic 3D reconstruction method
10.3.2 Character recognition method based on deep learning
10.4 Detection results
10.4.1 Defect detection result