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Advances in Optical Form and Coordinate Metrology
| Advances in Optical Form and Coordinate Metrology |
| Autore | Leach Richard |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bristol : , : Institute of Physics Publishing, , 2021 |
| Descrizione fisica | 1 online resource (229 pages) |
| Altri autori (Persone) |
SeninNicola
CatalucciSofia IsaMohammed A PianoSamanta Sims-WaterhouseDanny ChenRui XuJing ZhangSong EastwoodJoe |
| Collana | IOP Series in Emerging Technologies in Optics and Photonics Series |
| ISBN | 0-7503-4101-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- 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.
3.3 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. 5.3.1 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. 8.4 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. |
| Record Nr. | UNINA-9910861040103321 |
Leach Richard
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| Bristol : , : Institute of Physics Publishing, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Diagnostic imaging of mediastinal diseases / / Song Zhang, editor
| Diagnostic imaging of mediastinal diseases / / Song Zhang, editor |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIII, 268 p. 412 illus., 165 illus. in color.) |
| Disciplina | 616.0757076 |
| Soggetto topico |
Mediastinum - Imaging
Mediastinum - Diseases - Diagnosis Radiology |
| ISBN | 981-15-9930-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Thymic Hyperplasia -- Thymic Cyst -- Epithelial Tumor of Thymus -- Thymic Neuroendocrine Tumor -- Mediastinal Lymphoma -- Mediastinal Granulocytic Sarcoma -- Mediastinal Germ Cell Tumor -- Mediastinal Soft Tissue Tumor -- Neurogenic Tumor -- Intrapulmonary Lymph Nodes.-Metasatic Calcification -- Amylpodosis -- Fat Embolism Syndrom -- Lung Diseases Associated with IgG4 -- Endometriosis -- Extramedullary Hematopoiesis -- Plasma Cell Tumor -- Castleman Disease. |
| Record Nr. | UNINA-9910484045603321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sample size calculations for clustered and longitudinal outcomes in clinical research / / Chul Ahn, University of Texas Southwestern Medical Center, Dallas Texas, USA, Moonseong Heo, Albert Einstein College of Medicine, Bronx, New York, USA, Song
| Sample size calculations for clustered and longitudinal outcomes in clinical research / / Chul Ahn, University of Texas Southwestern Medical Center, Dallas Texas, USA, Moonseong Heo, Albert Einstein College of Medicine, Bronx, New York, USA, Song |
| Autore | Ahn Chul |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press : , : Taylor & Francis Group, , 2015 |
| Descrizione fisica | 1 online resource (252 p.) |
| Disciplina | 616.0072 |
| Collana | Chapman and Hall/CRC Biostatistics Series |
| Soggetto topico | Biometry |
| ISBN |
0-429-09768-9
1-4665-5627-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Contents; Preface; List of Figures; List of Tables; Chapter 1: Sample Size Determination for Independent Outcomes; Chapter 2: Sample Size Determination for Clustered Outcomes; Chapter 3: Sample Size Determination for Repeated Measurement Outcomes Using Summary Statistics; Chapter 4: Sample Size Determination for Correlated Outcome Measurements Using GEE; Chapter 5: Sample Size Determination for Correlated Outcomes from Two-Level Randomized Clinical Trials; Chapter 6: Sample Size Determination for Correlated Outcomes from Three-Level Randomized Clinical Trials; Bibliography
Back Cover |
| Record Nr. | UNINA-9910787244003321 |
|
Ahn Chul
|
||
| Boca Raton, FL : , : CRC Press : , : Taylor & Francis Group, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sample size calculations for clustered and longitudinal outcomes in clinical research / / Chul Ahn, University of Texas Southwestern Medical Center, Dallas Texas, USA, Moonseong Heo, Albert Einstein College of Medicine, Bronx, New York, USA, Song
| Sample size calculations for clustered and longitudinal outcomes in clinical research / / Chul Ahn, University of Texas Southwestern Medical Center, Dallas Texas, USA, Moonseong Heo, Albert Einstein College of Medicine, Bronx, New York, USA, Song |
| Autore | Ahn Chul |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press : , : Taylor & Francis Group, , 2015 |
| Descrizione fisica | 1 online resource (252 p.) |
| Disciplina | 616.0072 |
| Collana | Chapman and Hall/CRC Biostatistics Series |
| Soggetto topico | Biometry |
| ISBN |
1-04-005945-7
0-429-09768-9 1-4665-5627-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Contents; Preface; List of Figures; List of Tables; Chapter 1: Sample Size Determination for Independent Outcomes; Chapter 2: Sample Size Determination for Clustered Outcomes; Chapter 3: Sample Size Determination for Repeated Measurement Outcomes Using Summary Statistics; Chapter 4: Sample Size Determination for Correlated Outcome Measurements Using GEE; Chapter 5: Sample Size Determination for Correlated Outcomes from Two-Level Randomized Clinical Trials; Chapter 6: Sample Size Determination for Correlated Outcomes from Three-Level Randomized Clinical Trials; Bibliography
Back Cover |
| Record Nr. | UNINA-9910825038803321 |
|
Ahn Chul
|
||
| Boca Raton, FL : , : CRC Press : , : Taylor & Francis Group, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||