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  • Produktbild: Computer Vision for Electronics Manufacturing
  • Produktbild: Computer Vision for Electronics Manufacturing

Computer Vision for Electronics Manufacturing

Aus der Reihe Advances in Computer Vision and Machine Intelligence

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.09.2011

Verlag

Springer Us

Seitenzahl

340

Maße (L/B/H)

22,9/15,2/1,9 cm

Gewicht

505 g

Auflage

Softcover reprint of the original 1st ed. 1990

Sprache

Englisch

ISBN

978-1-4612-7841-2

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.09.2011

Verlag

Springer Us

Seitenzahl

340

Maße (L/B/H)

22,9/15,2/1,9 cm

Gewicht

505 g

Auflage

Softcover reprint of the original 1st ed. 1990

Sprache

Englisch

ISBN

978-1-4612-7841-2

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Computer Vision for Electronics Manufacturing
  • Produktbild: Computer Vision for Electronics Manufacturing
  • and Organization of the Book.- I. Applications and Systems Aspects.- 1. Vision System Components.- 1.1. Video Sensors.- 1.1.1. Video Cameras.- 1.1.2. Charge Transfer Devices (CTD).- 1.1.3. Shape of the Sensor.- 1.1.4. Sensor Resolution.- 1.1.5. Sensitivity.- 1.1.6. Dynamic Range.- 1.1.7. Signal-to-Noise Ratio (SNR).- 1.1.8. Geometric Distortion.- 1.1.9. Readout Speed.- 1.1.10. Spectral Sensitivity.- 1.1.11. Lag.- 1.1.12. Camera Synchronization.- 1.1.13. Nonuniformities.- 1.2. CCIR 625 Video Standard.- 1.3. Scanning of the Digitized Image.- 1.4. Strobe Lighting.- 1.4.1. Introduction.- 1.4.2. Motion Freeze.- 1.4.3. Flash Selection.- 1.4.4. Strobe Synchronization.- 1.4.5. Strobe Beam Geometry Configuration.- 1.4.6. Reflection Elimination.- 1.5. Image Content and Imperfections.- 1.5.1. Imperfections.- 1.5.2. Lighting Environments.- 1.5.3. Lighting Design.- 1.5.4. Image Compensation for Spatial Emissivity.- 1.6. Design Choices for the Vision System Specifications.- 1.6.1. Performance Requirements (R).- 1.6.2. Architecture (A).- 1.6.3. Vision System Design and Test Aids.- 1.7. Calculation of the Inspection Yield.- 1.7.1. Defect Detection Probability.- 1.7.2. Defect Probability from Area and Image Density.- 1.8. Total Inspection Costs.- 2. Imaging Microscopes for Microelectronics.- 2.1. Optical Microscope Attributes for Microelectronics.- 2.1.1. Microscope Lighting.- 2.1.2. Confocal Imaging.- 2.2. Electron Beam Inspection of ICs.- 2.2.1. Principle of Scanning Electron Microscopy (SEM).- 2.2.2. Voltage Resolution.- 2.2.3. Stroboscopy.- 2.2.4. Dynamic Fault Imaging (DFI) for Timing Problem Analysis.- 2.2.5. Thermal Gradient Imaging of Junctions.- 2.2.6. Scanning Transmission Electron Microscopy (STEM) for Cross-Sectional Analysis.- 2.3. Laser Scan Microscopy.- 2.3.1. Principle of Laser Scan Microscopy (LSM).- 2.3.2. Laser Spot Size.- 2.3.3. Laser Scanning Tomography (LST).- 2.3.4. Applications.- 2.4. Pulsed IR Microscopy.- 2.4.1. Dynamic Latch-Up Imaging.- 2.4.2. Static Substrate and Circuit Analysis.- 2.5. Imaging of Photoinduced Currents.- 2.5.1. Optical Beam-Induced Current (OBIC) Measurements.- 2.5.2. Laser-Based OBIC Photocurrent Calculation.- 2.5.3. Electron Beam-Induced (EBIC) Photocurrent Calculation.- 2.5.4. OBIC and EBIC Image Processing.- 3. Metrology in Electronic Devices and Substrates.- 3.1. Linewidth Measurement.- 3.2. Area Measurement.- 3.3. Surface Flatness and Profiling.- 3.3.1. Flatness Measures.- 3.3.2. Flatness Measurement.- 3.3.3. Flatness Display Images.- 3.3.4. Areas of Application.- 4. Inspection of Integrated Circuits and Gate Arrays.- 4.1. Inspection Standards.- 4.2. Inspection Procedure Implementation.- 4.3. Optical Setups for MIL-STD-883 Inspection Screens.- 4.4. Test Patterns.- 4.5. Optical Defect Features.- 4.6. Other Silicon IC Inspection Principles.- 4.7. Other III–V Compound IC Inspection Principles.- 4.8. Results of IC Inspection and Link to Other Test or Defect Analysis Methods.- 4.9. Surface and Depth Analysis of Semiconductors.- 4.9.1. Wavelength Dispersive X-Ray Spectrometry (WDX).- 4.9.2. Energy Dispersive X-Ray Spectrometry (EDX).- 4.9.3. Optical Beam-Induced Currents (OBIC).- 4.9.4. Photovoltage Spectroscopy (PVS).- 4.9.5. Deep-Level Transient Spectroscopy (DLTS).- 4.9.6. Secondary Ion Mass Spectrometry (SIMS).- 4.9.7. “Time-of-Flight” Mass Spectrometry.- 4.9.8. Scanning Auger Electron Spectrometry (SAM).- 4.10. Bubble Memory Inspection.- 4.11. Laser Trimming and Link Cutting.- 4.12. Inspection Implementation Aspects.- 4.13. Links between Inspection and Functional Testing.- 5. Sensor Fusion for Integrated Circuit Testing.- 5.1. Integrated Testing of ICs: Principles.- 5.2. Implementation of Integrated Precap Testing of Silicon ICs in Two IR Bands.- 5.3. Image Understanding of Defects in GaAs ICs by Sensor Fusion.- 5.3.1. Experimental Setup.- 5.3.2. Digital Image Processing.- 5.3.3. Knowledge-Based Interpretation.- 5.3.4. Experimental Results for III-V Compounds and Defect Correlation.- 6. Wafer Inspection.- 6.1. X-Y-Z Stage or Step-and-Repeat Accuracy.- 6.2. Wafer Flatness.- 6.3. Step Height Profile Mapping on Wafers.- 6.4. Nonetched Wafer Surface Inspection.- 6.5. Spatial Sampling in Nonetched Wafer Surface Inspection Systems.- 6.6. Wafer Probe Mark Inspection.- 6.7. Critical Dimensions and Macro Defect Inspection of Resist Patterns.- 7. Mask Repair and Inspection.- 7.1. Mask Repair.- 7.2. Mask Particle Detection or Reticle Error Check.- 7.3. Mask Metrology.- 7.4. Dual-Beam Mask Inspection.- 8. Knowledge-Based Processing.- 8.1. Principle of Knowledge-Based Processing.- 8.2. Architecture of a Knowledge-Based System.- 8.2.1. Knowledge Base (KB).- 8.2.2. Knowledge Representation (KR).- 8.2.3. Inference Procedure (IE).- 8.2.4. User and System Interfaces.- 8.3. Environmental Stress Knowledge Bases.- 9. Design Rule Verification.- 9.1. Introduction.- 9.2. Logic Architecture of Design Rule Verification Systems.- 9.3. Geometrical Attributes.- 9.4. Geometrical Validation Predicates.- 9.5. Electrical Validation Predicates.- 9.5.1. Circuit Extraction.- 9.5.2. Functional Testing.- 10. Printed Circuit Board (PCB) Inspection.- 10.1. Typical PCB Defects and Inspection Requirements.- 10.2. PCB Inspection Approaches.- 10.3. PCB Inspection System Architecture.- 10.4. PCB Illumination.- 10.5. PCB Annular Ring Inspection.- 10.6. PCB Conductor Width Measurement.- 10.7. Vision Feedback for PCB Drilling.- 10.8. Other PCB Inspection Sensors.- 10.9. Infrared PCB Inspection.- 10.10. Inspection of Multilayer Substrates.- 10.10.1. Introduction.- 10.10.2. Multilayer Inspection Approaches.- 10.11. Microfocus X-Ray Inspection of Multilayer PCBs.- 11. Inspection for Assembly Tasks.- 11.1. Mark Reading.- 11.2. 2-D Package Inspection (Lead, Label, Package Material).- 11.3. 3-D Package Inspection by Range/Intensity Images.- 11.4. Die Attach, Solder, and Bonding Inspection.- 11.5. Component Placement.- 11.5.1. Applications.- 11.5.2. SMD Placement.- 11.6. Missing or Improperly Mounted Components or Leads.- 11.6.1. Stuffed PCB Inspection.- 11.6.2. Other Applications.- 12. Knowledge-Based Printed Circuit Board Manufacturing.- 12.1. PCB Design.- 12.1.1. PCB Design Verification and Routing.- 12.1.2. PCB Layout.- 12.2. Bare-Board PCB Production.- 12.2.1. Tooling.- 12.2.2. PCB Inspection.- 12.2.3. Parts and Materials Transport.- 12.2.4. PCB/PWB Assembly Operations.- 12.3. Intelligent Wave Soldering.- 12.4. Stuffed PCB Inspection.- 12.5. Test and Rework.- 12.6. Integration.- 12.6.1. Configuration.- 12.6.2. Final Testing.- II. Vision Algorithms for Electronics Manufacturing.- 13. Image Quantization and Thresholding.- 13.1. Algorithm Quant-1: Quantization.- 13.2. Algorithm LUT-1: Lookup Table (LUT) Transforms.- 13.3. Algorithm Pseudo-1: Pseudo-Color Display.- 13.4. Algorithm Thresh-1: Fixed Threshold and Binarization.- 13.5. Algorithm Thresh-2: Threshold Selection by the Difference Histogram.- 14. Geometrical Corrections.- 14.1. Algorithm Geom-1: Geometrical Correction.- 14.2. Algorithm Geom-2: Interpolation.- 14.3. Algorithm Geom-3: Subpixel Edge Interpolation.- 14.4. Algorithm Calib-1: Sensor Calibration.- 15. Image Registration and Subtraction.- 15.1. Registration Problems.- 15.1.1. Registration Subproblems.- 15.1.2. Registration Procedures.- 15.1.3. Registration Errors.- 15.1.4. Registration versus Scan Type.- 15.1.5. Avoiding Registration.- 15.2. Algorithm Reg-1: Correlation.- 15.3. Algorithm Reg-2: Sequential Similarity Detection.- 15.4. Algorithm Templ-1: Physical Templates.- 15.5. Algorithm Circle-1: Circle Fitting.- 15.6. Algorithm Reg-3: Multiple Resolution Alignment.- 15.7. Algorithm Offset-1: Offset Calculation from Line Intersections for Fast Alignment.- 15.8. Algorithm Ruler-1: Validation of a Geometrical Model.- 15.9. Algorithm Subtr-1: Image Subtraction.- 16. Edge and Line Detection.- 16.1. Categorization of Algorithms.- 16.2. Algorithm Edge-1: Filtering-Based Edge Detection.- 16.3. Algorithm Edge-2: Edge Labeling for Line Detection.- 16.4. Algorithm Edge-3: Subpixel Edge Extraction.- 16.5. Algorithm Edge-4: Pyramidal Edge Detection.- 16.6. Algorithm Line-1: Edge Tracking.- 17. Region Segmentation and Boundaries.- 17.1. Introduction.- 17.2. Algorithm Segm-1: Region Growing.- 17.3. Algorithm Segm-2: Feature Domain Clustering.- 17.4. Algorithm Segm-3: Spatial Clustering.- 17.5. Algorithm Bound-1: Detection and Tracking of Boundaries.- 17.6. Algorithm Bound-2: Region Boundary Extraction.- 17.7. Algorithm AOI-1: Area of Interest (AOI) Processing.- 18. Geometry of Connected Components and Morphomathematics.- 18.1. Introduction.- 18.1.1. Goal.- 18.1.2. Adjacency (Connectedness) Relations.- 18.1.3. Labeled Image.- 18.1.4. Connected Components in Binary Images.- 18.2. Algorithm Label-1: Labeling of Connected Components in Binary Images.- 18.3. Algorithm Label-2: Relaxation Labeling.- 18.4. Algorithm Label-3: Position of a Connected Component.- 18.5. Algorithm Morph-1: Erosion and Dilation Operators.- 18.6. Algorithm Morph-2: Expansion-Contraction Flaw Detection.- 18.7. Algorithm Skeleton-1: Skeleton of a Connected Component.- 18.8. Algorithm Shrink-1: Shrinking of Connected Components or Lines.- 18.9. Algorithm Bridge-1: Matching Bridges in the Topological Cell Layouts.- 19. Feature Extraction.- 19.1. Introduction.- 19.2. Algorithm Feature-1: Attributes of a Connected Component.- 19.3. Algorithm Feature-2: Histogram Features of a Region.- 19.4. Algorithm Moments-1: Calculation of Moments of a Connected Component or Line.- 19.5. Algorithm Moments-2: Shape of a Line in Polar Coordinates.- 19.6. Algorithm Fuzzy-1: Figure of Merit for the IC Cell from a Fuzzy Language Description.- 19.7. Algorithm Feature-3: Binary Neighborhood Features.- 19.8. Algorithm Text-1: Texture Features.- 19.9. Algorithm Shade-1: Shade Features.- 20. Decision Logic.- 20.1. Algorithm Class-1: Pattern Classification.- 20.2. Algorithm Rule-1: Rule-Based Classification.- 21. Image Data Structures and Management.- 21.1. Algorithm Chain-1: Chain Code Representation of a Line.- 21.2. Algorithm Buff-1: Filtering Operations with Circular Buffering.- 21.3. Algorithm CAD-1: CAD Data Organization for Image Data Comparison.- 21.4. Algorithm Drill-1: Hole Drill Tape Organization.- 21.5. Algorithm Pat-1: File and Video Manipulations of Geometrical Reference Patterns.- 22. Conclusion: The Future of Computer Vision for Electronics Manufacturing.- Appendixes.- A. Glossary and Abbreviations.- B. Relevant Journals.- C. Units and Conversion Tables.- References.- Suggested Readings.