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Memorial University of Newfoundland Faculty of Engineering & Applied Science Engineering 7928

Memorial University of Newfoundland Faculty of Engineering & Applied Science Engineering 7928 Computer-Aided Engineering INTRODUCTION TO MACHINE VISION II Prof. Nick Krouglicof. Presentation Outline. Machine vision systems for mechanical metrology Algorithms for camera calibration

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Memorial University of Newfoundland Faculty of Engineering & Applied Science Engineering 7928

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  1. Memorial University of Newfoundland Faculty of Engineering & Applied Science Engineering 7928 Computer-Aided Engineering INTRODUCTION TO MACHINE VISION II Prof. Nick Krouglicof Memorial University of Newfoundland

  2. Presentation Outline • Machine vision systems for mechanical metrology • Algorithms for camera calibration • Development of 3D vision systems for MI Flume Tank • Industrial Applications of Machine Vision • High speed, line scan camera-based inspection system for the food processing industry • Vision based inspection of liquid crystal display (LCD) modules Memorial University of Newfoundland

  3. A systematic approach to the calibration of machine vision systems for industrial metrology • In the field of machine vision, camera calibration refers to the experimental determination of a set of parameters which describe the image formation process for a given analytical model of the machine vision system. • Ideally, camera calibration is performed without specialized optical equipment, without modifications to the hardware, and without a priori knowledge of the vision system. • Most calibration techniques are based on the observation of planar (2D) targets with a large number of control points. Memorial University of Newfoundland

  4. A systematic approach to the calibration of machine vision systems for industrial metrology The machine vision parameters which must be identified include : a) The scale factor b) The frame buffer coordinates of the image center c) The effective focal length of the lens-camera assembly d) The radial and tangential lens distortion coefficients e) The pose (position and orientation) of the camera Parameters a) through d) are classified as intrinsic, e) as extrinsic. Memorial University of Newfoundland

  5. A systematic approach to the calibration of machine vision systems for industrial metrology Memorial University of Newfoundland

  6. A systematic approach to the calibration of machine vision systems for industrial metrology Memorial University of Newfoundland

  7. An Efficient Camera Calibration Technique Offering Robustness and Accuracy Over a Wide Range of Lens Distortion Memorial University of Newfoundland

  8. An Efficient Camera Calibration Technique Offering Robustness and Accuracy Over a Wide Range of Lens Distortion CALIBRATION ACCURACY AND THE LENS DISTORTION MODEL Memorial University of Newfoundland

  9. Underwater 3D Vision Systems for MI Flume Tank Memorial University of Newfoundland

  10. Prototype Underwater Stereo Vision System Memorial University of Newfoundland

  11. Calibration Target for Underwater Stereo Vision System Memorial University of Newfoundland

  12. Development of an Intelligent 3D Vision System for Underwater Environment through Actively Manipulated Laser Triangulation Memorial University of Newfoundland

  13. Development of an Intelligent 3D Vision System for Underwater Environment through Actively Manipulated Laser Triangulation Memorial University of Newfoundland

  14. Industrial Machine Vision Applications Memorial University of Newfoundland

  15. Image Analysis Tools for Automated Inspection in the Food Processing Industry: X-Ray Enhancement Memorial University of Newfoundland

  16. Image Analysis Tools for Automated Inspection in the Food Processing Industry: Multispectral Imaging Memorial University of Newfoundland

  17. Image Analysis Tools for Automated Inspection in the Food Processing Industry: Multispectral Imaging Memorial University of Newfoundland

  18. High Speed, Line Scan Based Inspection System Memorial University of Newfoundland

  19. Line Scan Based Inspection System: Specifications • Objective: To remove defects (I.e. visible, dark particle larger than 0.007”) from apple sauce • System must be able to handle 12 metric tons per 8 hour shift • System must remove 95% of visible defects Memorial University of Newfoundland

  20. High Speed, Line Scan Based Inspection System • 2 distinct challenges: • Detection • Removal Memorial University of Newfoundland

  21. High Speed, Line Scan Based Inspection System Memorial University of Newfoundland

  22. High Speed, Line Scan Based Inspection System Memorial University of Newfoundland

  23. Line Scan Based Detection System • Detection system based on a high performance line scan camera; 4096 pixels per line at 4800 lines per second. • Image acquisition and processing functions implemented on a Complex Programmable Logic Device (CPLD) as opposed to a microprocessor or Digital Signal Processor (DSP). • The objective is to implement image processing functions with dedicated logic gates (i.e. hardware) for real-time performance. Memorial University of Newfoundland

  24. What are CPLDs? • Complex Programmable Logic Devices (CPLDs) are a class of programmable logic device that are commonly used to implement complex digital designs on a single integrated circuit. • Applications of CPLDs in the field of computer engineering include the implementation of bus controllers, address decoders, priority encoder and state machines Memorial University of Newfoundland

  25. Line Scan Camera-Based Detection System Memorial University of Newfoundland

  26. Line Scan Camera-Based Detection System Memorial University of Newfoundland

  27. Line Scan Camera-Based Detection System Typical section of apple sauce recorded with an area scan camera Typical Particle Memorial University of Newfoundland

  28. Line Scan Camera-Based Detection System Memorial University of Newfoundland

  29. Line Scan Camera-Based Detection System Memorial University of Newfoundland

  30. Removal System Memorial University of Newfoundland

  31. Removal System Memorial University of Newfoundland

  32. Removal System: Flow Characterization • Rheological nomenclature and associated velocity profiles for steady flow through tubes with circular cross section. Memorial University of Newfoundland

  33. Viscosity Measurement Memorial University of Newfoundland

  34. Viscosity Measurement Velocity profile can be characterized by power law! Memorial University of Newfoundland

  35. Flow Profile of Apple Sauce Memorial University of Newfoundland

  36. Particle Removal Window Memorial University of Newfoundland

  37. System Timing Diagram Memorial University of Newfoundland

  38. Aspiration Valve Characterization Memorial University of Newfoundland

  39. Aspiration Valve Characterization Memorial University of Newfoundland

  40. Particle Detection Rate Versus Flowrate Memorial University of Newfoundland

  41. High Speed, Line Scan Based Inspection System: Current Status • Industrial partner is currently developing the production version of the system. • Packaging of the principle components (i.e., lenses, cameras, electronics, light sources) remains a major challenge given the environment. • One possible solution is to integrate all the electronics in the camera enclosure. • Partner is anxious to explore applications in the pulp and paper industry. Memorial University of Newfoundland

  42. Vision Based Inspection of Liquid Crystal Display (LCD) modules • Objective: to automate the inspection of LCD modules in order to improve quality control • One step in the implementation of a Six-Sigma Program (“3.4 defects per million opportunities”) • The inspection must be completed within 30 seconds for 10 predetermined LCD patterns • System can “learn” new LCD modules without modifying software Memorial University of Newfoundland

  43. Vision Based Inspection of LCD modules: System Components • Pulnix camera with macro lens • High frequency fluorescent light sources • Coreco Bandit integrated image acquisition and VGA accelerator • Software developed using with WiT graphical programming environment in combination with Microsoft VB Memorial University of Newfoundland

  44. Vision Based Inspection of Liquid Crystal Display (LCD) modules Memorial University of Newfoundland

  45. Vision Based Inspection of Liquid Crystal Display (LCD) modules Original Image Showing Error in Alignment Memorial University of Newfoundland

  46. Vision Based Inspection of Liquid Crystal Display (LCD) modules Thresholding Operation – Image Subtraction with respect to an image with no segments illuminated Memorial University of Newfoundland

  47. Vision Based Inspection of Liquid Crystal Display (LCD) modules Blob Analysis – Reference Points are Identified Memorial University of Newfoundland

  48. Vision Based Inspection of Liquid Crystal Display (LCD) modules Image Rotation and Translation Memorial University of Newfoundland

  49. Vision Based Inspection of Liquid Crystal Display (LCD) modules Pixel by Pixel Image Subtraction from Reference Image – Thinning Operator Memorial University of Newfoundland

  50. Vision Based Inspection of Liquid Crystal Display (LCD) modules Blob Analysis Memorial University of Newfoundland

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