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Capabilities of Machine Vision Libraries

Capabilities of Machine Vision Libraries. Nasim Sajadi. Outline. What is Machine Vision. Aim : Simulate human vision ability Action: Analyse image information Requirement: Hardware , Software, and Cameras Combination of mathematics computer science artificial intelligence (AI)

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Capabilities of Machine Vision Libraries

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  1. Capabilities of Machine Vision Libraries NasimSajadi

  2. Outline

  3. What is Machine Vision • Aim : Simulate human vision ability • Action: Analyse image information • Requirement: • Hardware, Software, and Cameras • Combination of • mathematics • computer science • artificial intelligence (AI) • electronics • Limitations : • Dependency on the image quality

  4. Machine Vision vs. Computer Vision • Computer Vision • Research focus • Machine Vision • Industrial • Engineering focus

  5. Machine Vision in Industry • Repetitive • Defect recognition

  6. Machine Vision in Industry • Repetitive • Defect recognition

  7. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching

  8. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching

  9. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching

  10. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching • Measuring

  11. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching • Measuring

  12. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching • Measuring

  13. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching • Measuring • Continues • Monitoring

  14. Machine Vision in Industry • Repetitive • Defect recognition • Precise • Matching • Measuring • Continues • Monitoring

  15. Vision Technology Library

  16. HALCON • Machine Vision • MVTec Software GmbH • Comprehensive • Operators in C++, C, C#, Visual Basic and Delphi • HALCON IDE: HDevelop and HDevEngine

  17. OpenCV • Open source computer vision library me • Started by Intel • C/ C++ • Linux, Mac OS X and Windows ksk • Compatible with IPL & IPP • Research & Industry

  18. Sherlock • Machine Vision • Teledyne DALSA • Windows-based • Versions • Essential • Professional • Uses MVTools library

  19. Methodology • Taxonomy • Extracting concepts & algorithms from documentations • Evaluation • Taxonomy >> Coverage (depth & breadth) • Documentation >> strong

  20. Good Taxonomy • Good Taxonomy is • Comprehensive • simple • easy to understand and apply

  21. Taxonomy

  22. Taxonomy

  23. Taxonomy

  24. Taxonomy

  25. Taxonomy

  26. Taxonomy

  27. Taxonomy

  28. Taxonomy

  29. Taxonomy

  30. Coverage of Algorithms (Low Level)

  31. Coverage of Algorithms (Intermediate Level)

  32. Coverage of Algorithms (High Level)

  33. Documentation

  34. Recommendations

  35. Conclusion & Future Work • What we did • Taxonomy • Evaluation • Future Work • Speed • Code quality • Correction

  36. Questions??

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