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 results 10.4.2 Character recognition results References 11 Image Quality Improvement for Underwater Visual Inspections 11.1 Introduction 11.2 ACE and DCP model 11.2.1 ACE algorithm 11.2.2 DCP with brightness correction 11.3 Underwater images of visual inspection 11.4 Results analyzes 11.4.1 Qualitative evaluation 11.4.2 Quantitative evaluation 11.4.3 Field application References 12 The Visual Inspection of Defects in Nuclear Power Plant Reactors 12.1 Introduction 12.2 Visual examination of NPP reactors 12.3 Photometric stereo technique 12.4 D shape reconstruction of defects 12.4.1 Photometric stereo system 12.4.2 Estimation of light direction and intensity 12.4.3 D reconstruction using photometric stereo 12.5 Results analyzes References 13 Improved Visual Inspection for Nozzle Inner Radius based on Panoramic Imaging 13.1 Introduction 13.2 Detection of defects on nozzle inner radius of an RPV 13.3 Proposed panaromic imaging methods 13.3.1 Image mosaicking method 13.3.2 Image optimization method 13.3.3 Defect measurement method 13.4 Experimental evaluation References 14 Surface Quality Evaluation of Heavy and Medium Plate 14.1 Introduction 14.2 The surface defects formation and the partitioning of HMP 14.2.1 Analyzes of defects formation 14.2.2 Procedure for detecting flaws 14.2.3 Defects in partitioning 14.3 AHP evolution model 14.4 Results analyzes References 15 Intelligent Manufacturing Technology in the Steel Industry of China 15.1 Introduction 15.2 Intelligent manufacturing in the steel industry of China 15.2.1 General briefing on intelligent manufacturing in the steel industry 15.2.2 Aims for intelligent manufacturing 15.2.3 Framework for intelligent manufacturing
15.3 Typical models for intelligent manufacturing of steel industry 15.3.1 Rolling process intelligent manufacturing model 15.3.2 Steelmaking & Rolling process intelligent manufacturing model 15.4 Key technologies for intelligent manufacturing in steel industry 15.4.1 Online detection technologies 15.4.2 Quality controlling technology for the entire procedure of the steel industry 15.4.3 Equipment troubleshooting technology 15.4.4 Intelligent machinery References
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