20.7.3.3 Inspection -- Solder Joints, Welding, Pipes

Clocksin, W.F., Bromley, J.S.E., Davey, P.G., Vidler, A.R., Morgan, C.G.,
An Implementation of Model-Based Visual Feedback for Robot Arc Welding of Thin Sheet Steel,
IJRR(4), No. 1, 1985, pp. 13-26. BibRef 8500

Bartlett, S.L., Besl, P.J., Cole, C.L., Jain, R.C.[Ramesh C.], Mukherjee, D., and Skifstad, K.D.,
Automatic Solder Joint Inspection,
PAMI(10), No. 1, January 1988, pp. 31-43.
IEEE DOI BibRef 8801

Besl, P.J., Delp, E.J.[Edward J.], and Jain, R.C.[Ramesh C.],
Automatic Visual Solder Joint Inspection,
RA(1), March 1985. The facet model applied to inspection. BibRef 8503

Agapakis, J.E., Katz, J.M., Friedman, J.M., Epstein, G.N.,
Vision-Aided Robotic Welding: An Approach and a Flexible Implementation,
IJRR(9), No. 5, 1990, pp. 17-34. BibRef 9000

Kim, J.H., Cho, H.S.,
Neural-Network-Based Inspection of Solder Joints Using a Circular Illumination,
IVC(13), No. 6, August 1995, pp. 479-490.
Elsevier DOI BibRef 9508

Ruiz del Solar, J., Koppen, M.,
Sewage Pipe Image Segmentation Using a Neural-Based Architecture,
PRL(17), No. 4, April 4 1996, pp. 363-368. 9605
BibRef

Presern, S., and Gyergyek, L.,
An Intelligent Tactile Sensor: An On-Line Hierarchical Object and Seam Analyzer,
PAMI(5), No. 2, March 1983, pp. 217-220. BibRef 8303

Ryu, Y.K., Cho, H.S.,
New Optical Measuring System for Solder Joint Inspection,
OptLas(26), No. 6, 1997, pp. 487-514. 9701
BibRef

Kim, J.H., Cho, H.S., Kim, S.,
Pattern-Classification of Solder Joint Images Using a Correlation Neural-Network,
EngAAI(9), No. 6, December 1996, pp. 655-669. 9702
BibRef

Tarng, Y.S., Yeh, S.S., Juang, S.C.,
Fuzzy Pattern-Recognition of Tungsten Inert-Gas Weld Quality,
IJAMT(13), No. 6, 1997, pp. 387-392. 9708
BibRef

Yu, J.Y., Na, S.J.,
A Study on Vision Sensors for Seam Tracking of Height-Varying Weldment: Part 1: Mathematical-Model,
Mechatronics(7), No. 7, October 1997, pp. 599-612. 9801
BibRef

Cooper, D., Pridmore, T.P., Taylor, N.,
Towards the Recovery of Extrinsic Camera Parameters from Video Records of Sewer Surveys,
MVA(11), No. 2, October 1998, pp. 53-63.
Springer DOI 9811
BibRef

Zingaretti, P., Zanoli, S.M.,
Robust Real Time Detection of an Underwater Pipeline,
EngAAI(11), No. 2, April 1998, pp. 257-268. 9807
BibRef

Xu, K., Luxmoore, A.R., Davies, T.,
Sewer Pipe Deformation Assessment by Image-Analysis of Video Surveys,
PR(31), No. 2, February 1998, pp. 169-180.
Elsevier DOI 9802
BibRef

Kim, T.H.[Tae-Hyeon], Cho, T.H.[Tai-Hoon], Moon, Y.S.[Young Shik], Park, S.H.[Sung Han],
Visual inspection system for the classification of solder joints,
PR(32), No. 4, April 1999, pp. 565-575.
Elsevier DOI BibRef 9904

Boyer, K.L.[Kim L.], Ozguner, T.[Tolga],
Robust online detection of pipeline corrosion from range data,
MVA(12), No. 6, 2001, pp. 291-304.
Springer DOI 0106
BibRef

Aluze, D.[Denis], Merienne, F.[Fred], Dumont, C.[Christophe], Gorria, P.[Patrick],
Vision system for defect imaging, detection, and characterization on a specular surface of a 3D object,
IVC(20), No. 8, June 2002, pp. 569-580.
Elsevier DOI 0206
BibRef

Kaftandjian, V.[Valérie], Dupuis, O.[Olivier], Babot, D.[Daniel], Zhu, Y.M.[Yue Min],
Uncertainty modelling using Dempster-Shafer theory for improving detection of weld defects,
PRL(24), No. 1-3, January 2003, pp. 547-564.
Elsevier DOI 0211
BibRef

Shirai, Y.,
Automatic inspection of x-ray photograph of welding,
PR(1), No. 4, July 1969, pp. 257-258.
Elsevier DOI 0309
BibRef

Kim, J.H.[Jong Hyung],
Method and apparatus for inspecting solder joints,
US_Patent6,111,602, Aug 29, 2000
WWW Link. BibRef 0008

Michael, D.J.[David J.], Wallack, A.S.[Aaron S.],
Machine vision method using search models to find features in three-dimensional images,
US_Patent6,539,107, Mar 25, 2003
WWW Link. BibRef 0303

Iyer, S.[Shivprakash], Sinha, S.I.K.[Sun-Il K.],
A robust approach for automatic detection and segmentation of cracks in underground pipeline images,
IVC(23), No. 10, 20 September 2005, pp. 921-933.
Elsevier DOI 0509
BibRef

Sinha, S.I.K.[Sun-Il K.], Fieguth, P.W.[Paul W.],
Morphological segmentation and classification of underground pipe images,
MVA(17), No. 1, April 2006, pp. 21-31.
Springer DOI 0604
BibRef

Fieguth, P.W.[Paul W.], Sinha, S.I.K.[Sun-Il K.],
Automated analysis and detection of cracks in underground scanned pipes,
ICIP99(IV:395-399).
IEEE DOI BibRef 9900

Pachidis, T.P.[Theodore P.], Tarchanidis, K.N.[Kostas N.], Lygouras, J.N.[John N.], Tsalides, P.G.[Philippos G.],
Robot Path Generation Method for a Welding System Based on Pseudo Stereo Visual Servo Control,
JASP(2005), No. 14, 2005, pp. 2268-2280.
WWW Link. 0603
BibRef

Felisberto, M.K.[Marcelo Kleber], Lopes, H.S.[Heitor Silvério], Centeno, T.M.[Tania Mezzadri], Ramos de Arruda, L.V.[Lúcia Valéria],
An object detection and recognition system for weld bead extraction from digital radiographs,
CVIU(102), No. 3, June 2006, pp. 238-249.
Elsevier DOI Genetic algorithms; Radiographic 0605
BibRef

Chiu, S.N.[Shao-Nung], Perng, M.H.[Ming-Hwei],
Reflection-area-based feature descriptor for solder joint inspection,
MVA(18), No. 2, April 2007, pp. 95-106.
Springer DOI 0704
BibRef

Schalk, P., Ofner, R., O'Leary, P.,
Pipe eccentricity measurement using laser triangulation,
IVC(25), No. 7, 1 July 2007, pp. 1194-1203.
Elsevier DOI 0705
Eccentricity measurement; Laser triangulation; Metric vision; Circle fitting; Uncertainty BibRef

Kannala, J.H.[Ju-Ho], Brandt, S.S.[Sami S.], Heikkilä, J.[Janne],
Measuring and modelling sewer pipes from video,
MVA(19), No. 2, March 2008, pp. 73-83.
Springer DOI 0802
BibRef

Fennander, H.[Henri], Kyrki, V.[Ville], Fellman, A.[Anna], Salminen, A.[Antti], Kälviäinen, H.[Heikki],
Visual measurement and tracking in laser hybrid welding,
MVA(20), No. 2, February 2009, pp. xx-yy.
Springer DOI 0902
BibRef

Gao, X., Ding, D., Bai, T., Katayama, S.,
Weld-pool image centroid algorithm for seam-tracking vision model in arc-welding process,
IET-IPR(5), No. 5, 2011, pp. 410-419.
DOI Link 1108
BibRef

Herakovic, N.[Niko], Simic, M.[Marko], Trdic, F.[Francelj], Skvarc, J.[Jure],
A machine-vision system for automated quality control of welded rings,
MVA(22), No. 6, November 2011, pp. 967-981.
WWW Link. 1110
BibRef

Yun, J.P.[Jong Pil], Jeon, Y.J.[Yong-Ju], Choi, D.C.[Doo-Chul], Kim, S.W.[Sang Woo],
Real-time defect detection of steel wire rods using wavelet filters optimized by univariate dynamic encoding algorithm for searches,
JOSA-A(29), No. 5, May 2012, pp. 797-807.
WWW Link. 1202
BibRef

Jeon, Y.J.[Yong-Ju], Choi, D.C.[Doo-Chul], Lee, S.J.[Sang Jun], Yun, J.P.[Jong Pil], Kim, S.W.[Sang Woo],
Defect detection for corner cracks in steel billets using a wavelet reconstruction method,
JOSA-A(31), No. 2, February 2014, pp. 227-237.
DOI Link 1403
Industrial inspection; Algorithms BibRef

Wacker, E.S.[Esther-Sabrina], Denzler, J.[Joachim],
Enhanced anomaly detection in wire ropes by combining structure and appearance,
PRL(34), No. 8, June 2013, pp. 942-953.
Elsevier DOI 1305
BibRef
Earlier:
Combining Structure and Appearance for Anomaly Detection in Wire Ropes,
CAIP11(II: 163-170).
Springer DOI 1109
Anomaly detection; Image-based analysis; Surface inspection BibRef

Rzhanov, Y.[Yuri],
Photo-mosaicing of images of pipe inner surface,
SIViP(7), No. 5, September 2013, pp. 865-871.
WWW Link. 1309
BibRef

Dang, C., Gao, J., Wang, Z., Chen, F., Xiao, Y.,
Multi-step radiographic image enhancement conforming to weld defect segmentation,
IET-IPR(9), No. 11, 2015, pp. 943-950.
DOI Link 1511
adaptive equalisers BibRef

Yang, Z.Y.[Zhong-Yuan], Lu, S.H.[Shao-Hui], Wu, T.[Ting], Yuan, G.P.[Gong-Ping], Tang, Y.P.[Yi-Ping],
Detection of morphology defects in pipeline based on 3D active stereo omnidirectional vision sensor,
IET-IPR(12), No. 4, April 2018, pp. 588-595.
DOI Link 1804
BibRef

Idrobo-Pizo, G.A.[Gerardo A.], Motta, J.M.S.T.[José Maurício S.T.], Borges, D.L.[Díbio L.],
Novel invariant feature descriptor and a pipeline for range image registration in robotic welding applications,
IET-IPR(13), No. 6, 10 May 2019, pp. 964-974.
DOI Link 1906
BibRef

Vriesman, D.[Daniel], Britto, A.S.[Alceu S.], Zimmer, A.[Alessandro], Koerich, A.L.[Alessandro L.], Paludo, R.[Rodrigo],
Automatic visual inspection of thermoelectric metal pipes,
SIViP(13), No. 5, July 2019, pp. 975-983.
Springer DOI 1906
BibRef

Lahdenoja, O.[Olli], Säntti, T.[Tero], Poikonen, J.K.[Jonne K.], Laiho, M.[Mika], Paasio, A.[Ari], Pekkarinen, J.[Joonas], Salminen, A.[Antti],
Embedded processing methods for online visual analysis of laser welding,
RealTimeIP(16), No. 4, August 2019, pp. 1099-1116.
Springer DOI 1908
BibRef

Wang, S.H.[Shao-Hua], Sun, Y.[Yeran], Sun, Y.[Yinle], Guan, Y.[Yong], Feng, Z.H.[Zhen-Hua], Lu, H.[Hao], Cai, W.W.[Wen-Wen], Long, L.[Liang],
A Hybrid Framework for High-Performance Modeling of Three-Dimensional Pipe Networks,
IJGI(8), No. 10, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Zhang, L.[Lin], Zhang, Y.J.[Ying-Jie], Dai, B.C.[Bo-Chao], Chen, B.[Bo], Li, Y.F.[Yang-Fan],
Welding defect detection based on local image enhancement,
IET-IPR(13), No. 13, November 2019, pp. 2647-2658.
DOI Link 1911
BibRef

Zhu, J., Yuan, Z., Liu, T.,
Welding Joints Inspection via Residual Attention Network,
MVA19(1-5)
DOI Link 1911
feature extraction, inspection, production engineering computing, quality control, welding, welding joints inspection, Signal to noise ratio BibRef

Zou, Y.B.[Yan-Biao], Li, J.C.[Jin-Chao], Chen, X.Z.[Xiang-Zhi], Lan, R.[Rui],
Learning Siamese networks for laser vision seam tracking,
JOSA-A(35), No. 11, November 2018, pp. 1805-1813.
DOI Link 1912
Image processing, Image processing algorithms, Image quality, Joint transform correlators, Laser beams, Laser sensors BibRef

Xu, L.[Lei], Gong, J.[Jian], Na, J.M.[Jia-Ming], Yang, Y.W.[Yuan-Wei], Tan, Z.[Zhao], Pfeifer, N.[Norbert], Zheng, S.Y.[Shun-Yi],
Shield Tunnel Convergence Diameter Detection Based on Self-Driven Mobile Laser Scanning,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Yoo, Y.H.[Yong-Ho], Kim, U.H.[Ue-Hwan], Kim, J.H.[Jong-Hwan],
Convolutional Recurrent Reconstructive Network for Spatiotemporal Anomaly Detection in Solder Paste Inspection,
Cyber(52), No. 6, June 2022, pp. 4688-4700.
IEEE DOI 2207
Anomaly detection, Spatiotemporal phenomena, Printers, Image reconstruction, Decoding, Soldering, Inspection, surface mount technology (SMT) BibRef

Mlyahilu, J.N.[John N.], Mlyahilu, J.N.[Joseph N.], Lee, J.E.[Jae Eun], Kim, Y.B.[Young Bong], Kim, J.N.[Jong Nam],
Morphological geodesic active contour algorithm for the segmentation of the histogram-equalized welding bead image edges,
IET-IPR(16), No. 10, 2022, pp. 2680-2696.
DOI Link 2207
BibRef

Zhang, W.[Wanyuan], Zhou, T.[Tian], Li, J.[Jianghui], Xu, C.[Chao],
An Efficient Method for Detection and Quantitation of Underwater Gas Leakage Based on a 300-kHz Multibeam Sonar,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Zheng, Q.C.[Qing-Chun], Zhao, Y.Y.[Yang-Yang], Zhang, X.[Xu], Zhu, P.H.[Pei-Hao], Ma, W.P.[Wen-Peng],
A multi-view image fusion algorithm for industrial weld,
IET-IPR(17), No. 1, 2023, pp. 193-203.
DOI Link 2301
BibRef

Hosseiny, B.[Benyamin], Amini, J.[Jalal], Aghababaei, H.[Hossein], Ferraioli, G.[Giampaolo],
Enabling High-Resolution Micro-Vibration Detection Using Ground-Based Synthetic Aperture Radar: A Case Study for Pipeline Monitoring,
RS(15), No. 16, 2023, pp. 3981.
DOI Link 2309
BibRef

Cai, G.Q.[Guo-Qiang], Tajali, M.[Mosabreza], Zhang, M.[Miao], Jing, G.Q.[Guo-Qing],
Experimental Study of Static and Dynamic Loading Effects on Guided Wave-Based Intelligent Monitoring of Welded Rail Joints,
ITS(25), No. 6, June 2024, pp. 4892-4907.
IEEE DOI 2406
Rails, Monitoring, Rail transportation, Acoustics, Welding, Loading, Inspection, Signal processing, intelligent SHM, welded rail joint BibRef

Haurum, J.B.[Joakim Bruslund], Madadi, M.[Meysam], Escalera, S.[Sergio], Moeslund, T.B.[Thomas B.],
Multi-Task Classification of Sewer Pipe Defects and Properties using a Cross-Task Graph Neural Network Decoder,
WACV22(1441-1452)
IEEE DOI 2202
Water, Learning systems, Codes, Shape, Inspection, Multitasking, Vision Systems and Applications Multi-Task Classification BibRef

Fauzan, K.N., Suwardhi, D., Murtiyoso, A., Gumilar, I., Sidiq, T.P.,
Close-range Photogrammetry Method for Sf6 Gas Insulated Line (gil) Deformation Monitoring,
ISPRS21(B2-2021: 503-510).
DOI Link 2201
BibRef

Haurum, J.B.[Joakim Bruslund], Moeslund, T.B.[Thomas B.],
Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and Benchmark,
CVPR21(13451-13462)
IEEE DOI 2111
Measurement, Economics, Codes, Biological system modeling, Benchmark testing, Inspection BibRef

Molefe, M.[Mohale], Tapamo, J.R.[Jules-Raymond],
Classification of Rail Welding Defects Based on the Bag of Visual Words Approach,
MCPR21(207-218).
Springer DOI 2108
BibRef

Dong, X., Taylor, C.J., Cootes, T.F.,
Automatic Inspection of Aerospace Welds Using X-Ray Images,
ICPR18(2002-2007)
IEEE DOI 1812
Welding, Forestry, X-ray imaging, Inspection, Vegetation, Image edge detection, Training, random forests BibRef

Bae, J., Yeo, D., Yoon, D., Oh, S.W., Kim, G.J., Kim, N., Pyo, C.,
Deep-Learning-Based Pipe Leak Detection Using Image-Based Leak Features,
ICIP18(2361-2365)
IEEE DOI 1809
Leak detection, acoustic signal, image feature, deep-learning, residual network BibRef

Zhang, S., Stevenson, R.L.,
Inertia Sensor Aided Alignment for Burst Pipeline in Low Light Conditions,
ICIP18(3953-3957)
IEEE DOI 1809
Cameras, Pipelines, Noise measurement, Kalman filters, Covariance matrices, Feature extraction, Noise reduction, smartphone camera BibRef

Wu, X.J.[Xiao-Jun], Cao, K.[Kai], Gu, X.D.[Xiao-Dong],
A Surface Defect Detection Based on Convolutional Neural Network,
CVS17(185-194).
Springer DOI 1711
BibRef

Ye, S.F.[Shao-Feng], Guo, Z.Y.[Zhi-Ye], Zheng, P.[Peng], Wang, L.[Lei], Lin, C.[Chun],
A Vision Inspection System for the Defects of Resistance Spot Welding Based on Neural Network,
CVS17(161-168).
Springer DOI 1711
BibRef

Guo, Z.Y.[Zhi-Ye], Ye, S.F.[Shao-Feng], Wang, Y.J.[Yi-Ju], Lin, C.[Chun],
Resistance Welding Spot Defect Detection with Convolutional Neural Networks,
CVS17(169-174).
Springer DOI 1711
BibRef

Yang, J.J.[Jia-Jia], Wang, K., Wu, T.L.[Tong-Li], Zhou, X.X.[Xiao-Xiao],
Binocular stereovision system for three-dimensional reconstruction of aluminum alloy weld pool in pulsed GMA welding,
ICIVC17(536-540)
IEEE DOI 1708
Cameras, Image reconstruction, Metals, Sensors, Surface reconstruction, Surface treatment, Welding, aluminium alloy, binocular stereovision system, pulsed GMA welding, three-dimensional reconstruction, weld, pool BibRef

Heinemann, D., Baumgarten, D., Knabner, S.,
Low Cost Target Design and Detection for Camera Calibration in Image Based Close Range Inspection Applications,
ICVISP17(98-102)
IEEE DOI 1712
BibRef
Earlier: A1, A3, A2:
Single Image Camera Calibration In Close Range Photogrammetry For Solder Joint Analysis,
ISPRS16(B3: 27-30).
DOI Link 1610
Erbium, Nickel, Signal processing, calibration target, camera calibration, close range application, distance transform, marker detection BibRef

Pessoa, S.[Saulo], Cesar, V.[Vinicius], Reis, B.[Bernardo], Kelner, J.[Judith], Santos, I.[Ismael],
A Segmentation Technique for Flexible Pipes in Deep Underwater Environments,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Cesar, V.[Vinicius], Reis, B.[Bernardo], Pessoa, S.[Saulo], Kelner, J.[Judith], Santos, I.[Ismael],
Stereo Tracking and 3D Reconstruction of Underwater Pipes,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Goumeidane, A.B.[Aicha Baya], Bouzaieni, A.[Abdessalem], Nacereddine, N.[Nafaa], Tabbone, S.A.[Salvatore A.],
Bayesian Networks-Based Defects Classes Discrimination in Weld Radiographic Images,
CAIP15(II:554-565).
Springer DOI 1511
BibRef

Ekkel, T., Schmik, J., Luhmann, T., Hastedt, H.,
Precise Laser-Based Optical 3D Measurement of Welding Seams Under Water,
Underwater15(117-122).
DOI Link 1508
BibRef

Abe, R., Hamada, K., Hirata, N., Tamura, R., Nishi, N.,
Precisions Measurement for the Grasp of Welding Deformation Amount of Time Series for Large-Scale Industrial Products,
Seamless15(153-157).
DOI Link 1508
BibRef

Feliciano, F.F.[Flavio F.], Mainier, F.B.[Fernando B.], Leta, F.R.[Fabiana R.],
Possible use of texture parameters to corrosion evolution analysis,
WSSIP14(19-22) 1406
Chemicals BibRef

Tezerjani, A.D.[A. Dehghan], Mehrandezh, M., Paranjape, R.,
4-DOF pose estimation of a pipe crawling robot using a Collimated Laser, a conic mirror, and a fish-eye camera,
Southwest14(45-48)
IEEE DOI 1406
inspection BibRef

Goumeidane, A.B.[Aicha Baya], Nacereddine, N.[Nafaa],
Spatially Varying Weighting Function-Based Global and Local Statistical Active Contours. Application to X-Ray Images,
ACIVS16(181-192).
Springer DOI 1611
BibRef
Earlier:
Local and Global Statistics-Based Explicit Active Contour for Weld Defect Extraction in Radiographic Inspection,
CAIP13(II:491-498).
Springer DOI 1311
BibRef

Lahdenoja, O.[Olli], Säntti, T.[Tero], Poikonen, J.[Jonne], Laiho, M.[Mika], Paasio, A.[Ari],
Characterizing Spatters in Laser Welding of Thick Steel Using Motion Flow Analysis,
SCIA13(675-686).
Springer DOI 1311
BibRef

Bendicks, C.[Christian], Lilienblum, E.[Erik], Freye, C.[Christian], Al-Hamadi, A.[Ayoub],
Tracking of a Handheld Ultrasonic Sensor for Corrosion Control on Pipe Segment Surfaces,
ACIVS13(342-353).
Springer DOI 1311
BibRef

Fecker, D.[Daniel], Märgner, V.[Volker], Fingscheidt, T.[Tim],
Training of Classifiers for Quality Control of On-Line Laser Brazing Processes with Highly Imbalanced Datasets,
DAGM12(367-376).
Springer DOI 1209
BibRef

Michalak, M.[Marcin], Nurzynska, K.[Karolina], Pytlik, A.[Andrzej], Paczesniowski, K.[Krzysztof],
Analysis of Deformation of Mining Chains Based on Motion Tracking,
ISVC12(II: 588-596).
Springer DOI 1209
BibRef

Mapurisa, W.T., Sithole, G.,
Deformation Detection In Piping Installations Using Profiling Techniques,
AnnalsPRS(I-3), No. 2012, pp. 141-146.
DOI Link 1209
BibRef

Benedek, C.[Csaba],
Analysis of Solder Paste scooping with hierarchical point processes,
ICIP11(2121-2124).
IEEE DOI 1201
BibRef

Wang, Y.Y.[Yuan-You], Guo, Q.A.[Qi-Ang], Zhao, F.Y.[Fang-Yuan],
Research on the model of submarine cable route monitoring based on improved Petri Nets,
IASP11(640-644).
IEEE DOI 1112
BibRef

Jiang, D.[Daoyu], Guo, Q.A.[Qi-Ang], Zhang, C.[Cheng],
Research on modeling for submarine cable monitoring system based on timed colored Petri Nets,
IASP11(583-585).
IEEE DOI 1112
BibRef

Zuo, M.J.[Ming-Jiu], Tian, F.[Feng], Qiao, X.R.[Xiao-Rui],
Research of parallel placed submarine cable route detection method,
IASP11(595-599).
IEEE DOI 1112
BibRef

Fu, H.[Hao], Wu, B.[Bin], He, C.F.[Cun-Fu], Wang, W.B.[Wei-Bin],
A synthetic digital signal processing method of ultrasonic guided wave pipeline inspection,
IASP11(444-446).
IEEE DOI 1112
BibRef

Zhang, C.N.[Cheng-Ning], Xu, M.[Min], Zhao, M.Y.[Ming-Yang], Luo, H.B.[Hai-Bo],
On line quality inspection in tailor welded blank based on laws texture energy and structured light,
ICARCV10(207-212).
IEEE DOI 1109
BibRef

Baek, S.H.[Seung-Hae], Park, S.Y.[Soon-Yong],
A 3-D Tube Scanning Technique Based on Axis and Center Alignment of Multi-laser Triangulation,
ACIVS11(724-735).
Springer DOI 1108
Laser and camera, 360 deg of inside of tube. BibRef

Mashford, J., Rahilly, M., Davis, P.,
An Approach Using Mathematical Morphology and Support Vector Machines to Detect Features in Pipe Images,
DICTA08(84-89).
IEEE DOI 0812
BibRef

Barradas, I.[Ignacio], Garza, L.E.[Luis E.], Morales-Menendez, R.[Ruben], Vargas-Martínez, A.[Adriana],
Leaks Detection in a Pipeline Using Artificial Neural Networks,
CIARP09(637-644).
Springer DOI 0911
BibRef

Yuan, P.X.[Pei-Xin], Tan, J.[Jun],
Research on Image Recognition Method of In-Service Pipeline Corrosion Fault,
CISP09(1-6).
IEEE DOI 0910
BibRef

Hua, G.[Gang], Wang, H.Y.[Hong-Yao], Chen, F.J.[Feng-Jun], Lu, Y.H.[Yan-Hong], Xu, Z.[Zhao], Tian, J.[Jie], Zhou, B.B.[Bing-Bing],
Improving SNR of MFL Signal in Flaw Detection of Coal Mine Wire Ropes,
CISP09(1-6).
IEEE DOI 0910
BibRef

Li, J.[Jian], Chen, S.[Shili], Zhang, Y.[Yu], Jin, S.J.[Shi-Jiu], Wang, L.K.[Li-Kun],
Cross-Correlation Method for Online Pipeline Leakage Monitoring System,
CISP09(1-4).
IEEE DOI 0910
BibRef

Lin, X.L.[Xiong Lin], Zhong, W.[Wang], Zhong, W.X.[Wang Xin],
Research of Double-Threshold Segmentation of Brazing-Area Defect of Saw Based on Otsu and HSV Color Space,
CISP09(1-4).
IEEE DOI 0910
BibRef

Shao, J.X.[Jia-Xin], Du, D.[Dong], Zhu, X.J.[Xin-Jie], Wang, L.[Li],
Weld Slim Line Defects Extraction Based on Adaptive Local Threshold and Modified Hough Transform,
CISP09(1-5).
IEEE DOI 0910
BibRef

Zhan, X.L.[Xiang-Lin], Jin, S.J.[Shi-Jiu],
Signal Analysis Method for Automatic Flaw Classification on Pipeline Girth Weld Inspection by Ultrasonic Phased Array System,
CISP09(1-5).
IEEE DOI 0910
BibRef

Yan, H.B.[Han-Bing], Zhao, L.[Lina], Ju, H.[Hui],
Research on SVM Based Classification for Welding Defects in Radiographic Testing,
CISP09(1-5).
IEEE DOI 0910
BibRef

Goumeidane, A.B.[Aicha Baya], Khamadja, M.[Mohammed], Naceredine, N.[Nafaa],
Bayesian Pressure Snake for Weld Defect Detection,
ACIVS09(309-319).
Springer DOI 0909
BibRef

Esquivel, S.[Sandro], Koch, R.[Reinhard], Rehse, H.[Heino],
Reconstruction of Sewer Shaft Profiles from Fisheye-Lens Camera Images,
DAGM09(332-341).
Springer DOI 0909
BibRef

Yokoyama, H., Yamamoto, Y., Ebata, S.,
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IEEE DOI 0709
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García-Chamizo, J.M.[Juan Manuel], Fuster-Guilló, A.[Andrés], Azorín-López, J.[Jorge],
Simulation of Automated Visual Inspection Systems for Specular Surfaces Quality Control,
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Visual Input Amplification for Inspecting Specular Surfaces,
ICIP06(485-488).
IEEE DOI 0610
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Xu, D.[De], Jiang, Z.M.[Ze-Min], Wang, L.K.[Lin-Kun], Tan, M.[Min],
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ICARCV04(III: 1559-1563).
IEEE DOI 0412
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Li, L.P.[Lai-Ping], Chen, S.B.[Shan-Ben], Lin, T.[Tao],
3D vision technology and its applications in welding,
ICARCV04(I: 190-198).
IEEE DOI 0412
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O'Brien, D., Gupta, M., Gray, R.M., Hagene, J.K.,
Analysis and classification of internal pipeline images,
ICIP03(III: 577-580).
IEEE DOI 0312
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Duran, O., Althoefer, K., Seneviratne, L.D.,
A sensor for pipe inspection: model, analysis and image extraction,
ICIP03(III: 597-600).
IEEE DOI 0312
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Johnson, M.,
Real time pipeline profile extraction using recursive filtering and circle location,
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IEEE DOI 0312
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System Concept for Image Sequence Classification in Laser Welding,
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Hanton, K.[Karel], Smutný, V.[Vladimír], Franc, V.[Vojtch], Hlavá, V.[Václav],
Alignment of Sewerage Inspection Videos for Their Easier Indexing,
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Kolesnik, M.,
Visual orientation in the sewer: adaptation to the environment,
ICPR02(II: 856-859).
IEEE DOI 0211
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Kolesnik, M.[Marina], Baratoff, G.[Gregory],
Online Distance Recovery for a Sewer Inspection Robot,
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Anzalone, A., Gugliotta, G., Machi, A., Sardisco, G.,
Automatic quality control of industrial products for irrigation,
CIAP99(588-593).
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Takagi, Y., Medioni, G.,
Volumetric Description of Dip Solder Joints from Range Data,
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Arakawa, K., Kakizaki, T., Omyo, S.,
A Method of Robust Seam Feature Detection from Profiles for Robotic Sealing,
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Karlströms, M., Edholm, P.R., Magnusson Seger, M.,
Crack Detection in Tubes Using Filtered Linear Tomosynthesis,
SSAB97(Image Processing) 9703
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Kim, T.H., Cho, T.H., Moon, Y.S., Park, S.H.,
Automatic Inspection of Solder Joints Using Layered Illumination,
ICIP96(II: 645-648).
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Matsuyama, Y., Honda, T., Yamamura, H., Sasazawa, H., Nomoto, M., and Ninomiya, T.,
Automated Solder Joint Inspection System Using Optical 3D Image Detector,
WACV96(116-122).
IEEE DOI 9609
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Kim, T.H., Cho, T.H., Moon, Y.S., and Park, S.H.,
An Automated Visual Inspection of Solder Joints Using 2D and 3D Features,
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IEEE DOI 9609
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Greig, A.R.[Alistair R.],
Application of the Hough transform for weld inspection underwater,
CIAP95(731-736).
Springer DOI 9509
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Hanajík, M.[Milan], van Vliet, R.G.[Ruud G.],
Real time image processing for fast seam tracking,
CAIP93(698-705).
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Griffiths, E., Jordan, R.,
Automatic inspection of surface mount solder joints using X-ray images,
BMVC90(xx-yy).
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Odawara, G., Kurokawa, T., Tamiya, Y., Fujii, T.,
An Integrated Visual System for Solder Inspection,
ICPR88(II: 663-665).
IEEE DOI BibRef 8800

Nan, H., Abbott, M.G., Beattie, R.J.,
Approaches to Low Level Image Processing for Vision Guided Seam Tracking Systems,
ICPR88(I: 601-603).
IEEE DOI BibRef 8800

Nakagawa, Y., and Ninomiya, T.,
Three-Dimensional Vision Systems Using the Structured-Light Method for Inspecting Solder Joints and Assembly Robots,
3DMV87(543-564). BibRef 8700

Masaki, I.,
Seamsight: A Parallel/Pipelined Vision System for Seam Tracking,
ICPR84(424-427). BibRef 8400

Li, Z.R., Zhang, D.P., Dai, Q.K.,
To Detect The Defects In Welding Seam Using The Pattern Recognition,
ICPR84(942-944). BibRef 8400

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Inspection -- Metal Inspection, Castings, Machining .