LEADER 07923nam 22005413 450 001 9910861040103321 005 20240407090434.0 010 $a0-7503-4101-7 035 $a(MiAaPQ)EBC31253058 035 $a(Au-PeEL)EBL31253058 035 $a(CKB)31356173400041 035 $a(EXLCZ)9931356173400041 100 $a20240407d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Optical Form and Coordinate Metrology 205 $a1st ed. 210 1$aBristol :$cInstitute of Physics Publishing,$d2021. 210 4$dİ2020. 215 $a1 online resource (229 pages) 225 1 $aIOP Series in Emerging Technologies in Optics and Photonics Series 311 $a0-7503-2525-9 327 $aIntro -- Preface -- Editor biography -- Richard Leach -- List of contributors -- Chapter 1 Terms, definitions and standards -- 1.1 Introduction -- 1.2 Surface and coordinate terms and definitions -- 1.3 General metrology terms and definitions -- 1.4 Specification standards for coordinate metrology -- 1.4.1 Coordinate metrology standards -- Acknowledgements -- References -- Chapter 2 State-of-the-art in point cloud analysis -- 2.1 Introduction -- 2.1.1 Mathematical representation of 3D point clouds -- 2.1.2 Common 3D point cloud file formats -- 2.1.3 Point cloud transformations -- 2.2 Extracting properties and organising information in point clouds -- 2.2.1 Convex hull and bounding boxes -- 2.2.2 Centroid and principal axes of a point cloud -- 2.2.3 Spatial subdivision of point clouds -- 2.3 Point cloud pre-processing -- 2.3.1 Point cloud simplification, decimation and resampling -- 2.3.2 Elimination of isolated points and noise reduction -- 2.3.3 Triangle meshes and conversion to/from point clouds -- 2.4 Point features and partitioning -- 2.4.1 Point normals -- 2.4.2 Point curvatures -- 2.4.3 Partitioning and segmentation -- 2.5 Point cloud fitting -- 2.5.1 Fitting methods -- 2.6 Registration of point clouds -- 2.6.1 Registration based on external references or based on matching landmarks -- 2.6.2 The absolute orientation problem -- 2.6.3 Alignment by means of principal component analysis -- 2.6.4 RANSAC alignment -- 2.6.5 Alignment by iterative closest points -- 2.6.6 Landmark matching and alignment using similarity metrics -- 2.7 Measurement uncertainty in point cloud surface data -- 2.7.1 Approaches to the estimation of measurement uncertainty -- 2.7.2 Uncertainty associated with point clouds -- 2.8 Conclusions -- References -- Chapter 3 Laser triangulation -- 3.1 Laser triangulation -- 3.2 Laser triangulation sensors. 327 $a3.3 Laser triangulation measurement dependence on surface properties -- 3.3.1 Measurement uncertainty limit -- 3.3.2 Surface reflectance perspective -- 3.3.3 Measurement dependence on surface form -- 3.4 Laser triangulation systems -- 3.4.1 Extension of a point based laser triangulation sensor -- 3.4.2 Point measurement systems -- 3.4.3 Profile measurement systems -- 3.4.4 Surface measurement systems -- 3.4.5 Advanced laser triangulation systems -- 3.5 Working process of laser triangulation -- 3.5.1 Characterisation of intrinsic parameters -- 3.5.2 Characterisation of extrinsic parameters -- 3.5.3 Pre-calibration of laser triangulation systems -- 3.5.4 Scanning path planning -- 3.5.5 Image pre-processing -- 3.5.6 Laser feature extraction -- 3.5.7 Refinement and postprocessing -- 3.6 Application of laser triangulation measurements -- 3.6.1 Application of laser triangulation in emerging manufacturing methods -- 3.6.2 Application for geometric inspection -- 3.6.3 Application of 3D reconstructed models -- 3.7 Conclusions -- References -- Chapter 4 Close-range photogrammetry -- 4.1 Introduction -- 4.1.1 Modern photogrammetry -- 4.1.2 Camera projection theory -- 4.1.3 The pinhole camera model -- 4.1.4 Distortion modelling -- 4.2 Characterisation and calibration -- 4.2.1 Camera characterisation -- 4.2.2 Linear techniques -- 4.2.3 Non-linear methods -- 4.2.4 Self-calibration -- 4.3 System calibration -- 4.3.1 Arbitrary scale -- 4.4 Image acquisition -- 4.4.1 Depth of field -- 4.4.2 Imaging procedure optimisation -- 4.5 Summary -- References -- Chapter 5 Digital fringe projection profilometry -- 5.1 Introduction -- 5.2 Fringe pattern generation methods -- 5.2.1 Conventional fringe generation methods -- 5.2.2 Digital binary defocusing techniques -- 5.2.3 New fringe pattern generation methods -- 5.3 Fringe analysis. 327 $a5.3.1 Conventional fringe analysis techniques -- 5.3.2 Machine learning enhanced fringe analysis methods -- 5.4 Phase unwrapping -- 5.4.1 Conventional phase unwrapping methods -- 5.4.2 Non-conventional phase unwrapping methods -- 5.4.3 Machine-learning-based phase unwrapping methods -- 5.5 High dynamic range techniques -- 5.6 Calibration -- 5.6.1 Conventional methods -- 5.6.2 Recent developments -- 5.7 High-speed FPP realisation -- 5.7.1 Conventional high-speed FPP methods -- 5.7.2 Recent developments -- 5.8 Towards automation -- 5.9 Towards integrated solutions -- 5.9.1 3D imaging system for crime scene evidence collection -- 5.9.2 Robotic path planning -- 5.10 Summary -- References -- Chapter 6 Machine learning approaches -- 6.1 Introduction -- 6.2 Overview of machine learning and machine learning methods -- 6.3 Machine learning for stereo matching -- 6.3.1 Learned stereo machines -- 6.4 Machine learning for phase unwrapping -- 6.5 Learning depth from a single image -- 6.5.1 Characterisation of cameras and projectors -- 6.6 Machine learning for point cloud analysis -- 6.6.1 Point cloud segmentation -- 6.6.2 Point cloud registration -- 6.6.3 Point cloud completion -- 6.7 Conclusions -- References -- Chapter 7 Precision freeform metrology -- 7.1 Overview of freeform surfaces -- 7.2 Framework for precision freeform metrology -- 7.3 Characterisation of freeform surfaces -- 7.3.1 Surface fitting and reconstruction -- 7.3.2 Surface matching -- 7.3.3 Surface parameters for form error evaluation -- 7.4 Conclusions and future research -- Acknowledgments -- References -- Chapter 8 Performance verification for optical co-ordinate metrology -- 8.1 Introduction -- 8.2 Material measures -- 8.2.1 Material measure 1 -- 8.2.2 Material measure 2 -- 8.2.3 Material measure 3 -- 8.2.4 Material measure 4 -- 8.3 The different types of performance verification test. 327 $a8.4 Specification of errors -- 8.4.1 General guidelines for performance verification -- 8.5 Performance verification procedures -- 8.5.1 Measurements with representative points -- 8.5.2 General preparation for the performance verification test -- 8.5.3 Probing characteristics -- 8.5.4 Distortion characteristics -- 8.5.5 Length measurement errors -- 8.6 Compliance with specifications -- 8.6.1 Formal definition of performance verification -- 8.6.2 Retesting after a failed compliance with specifications -- 8.7 A final note on the validity of performance verification -- References. 330 $aAdvances in Optical Form and Coordinate Metrology covers the latest advances in the development of optical form and coordinate measuring instruments plus the manipulation of point cloud data. 410 0$aIOP Series in Emerging Technologies in Optics and Photonics Series 700 $aLeach$b Richard$0237366 701 $aSenin$b Nicola$0732441 701 $aCatalucci$b Sofia$01741236 701 $aIsa$b Mohammed A$01741237 701 $aPiano$b Samanta$01741238 701 $aSims-Waterhouse$b Danny$01741239 701 $aChen$b Rui$01457873 701 $aXu$b Jing$0788017 701 $aZhang$b Song$01732278 701 $aEastwood$b Joe$01741240 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910861040103321 996 $aAdvances in Optical Form and Coordinate Metrology$94167208 997 $aUNINA