Machine vision has progressed in leaps and bounds since the disappointments in the eighties with tremendous results achievable today. Nowadays, machine vision systems are highly effective and a key part of many industrial systems ranging from mineral processing to manufacturing. The fundamentals of image processing and machine vision are covered in the beginning to give everyone a solid foundation to work from. The program commences with an examination of optics and lighting - as the experts say - machine vision is easy if you can get a good image into the system. You will be shown how to select and design lighting to achieve the best contrast. The selection of cameras, frame grabbers and vision appliances are next covered in practical detail. Finally, you will be shown how to select and integrate all the varying components into a professional and working system.

The program will be presented with minimal use of mathematics and extensive use of practical concepts and applications. There will be extensive use of hands-on exercises ranging initially from illustrating the key concepts of image processing to setting up a complete working machine vision system. This approach will ensure that you maximise your learning experience on this program. However, despite the advances in technology, do not expect your machine vision to have the versatility and brilliance of a human… yet. But if you apply the key concepts in this program to your machine vision application, you should have a reliable and effective solution.

IN THIS 3-MONTH INTERACTIVE LIVE ONLINE COURSE YOU WILL LEARN:

  • The fundamentals of image processing and machine vision
  • How to develop a simple machine vision system
  • How to select cameras/lightning/frame grabbers and software
  • How to assess resolution requirements
  • Best practice in alignment and calibration procedures
  • Identification and correction for sources of error
  • How to design for harsh industrial applications
  • How to configure a machine vision system
  • The selection of optimal lightning to achieve best contrast
  • How to apply the best optics to achieve optimal resolution
  • How to do a simple design for high-speed real time performance
  • How to troubleshoot simple machine vision problems

Next intake starts May 04, 2015.

It is the only intake in 2015 so do not delay your opportunity to join this course.

There are limited places available so contact us now to secure your spot!

COURSE OUTLINE

MODULE 1: INTRODUCTION

  • Systems approach to machine vision
  • Machine vision vs. image processing
  • Computer vision vs. human vision
  • Basics of image processing
  • Pattern recognition
  • Filtering
  • Inverse filtering
  • Colour properties and the eye
  • Colour properties of image input and output devices

MODULE 2: DIGITAL IMAGE PROCESSING BASICS

  • Fast Fourier Transform
  • Digital Fast Fourier Transform
  • Sampling theory
  • Aliasing
  • Bits and pixel
  • Trade-offs

MODULE 3: MACHINE VISION SYSTEM COMPONENTS

  • Lighting, filters and optics
  • Image sensors
  • Image processing and analysis components
  • Mechanical interfaces

MODULE 4: LIGHTING

  • Lighting techniques
  • Light sources
  • Beyond visible spectrum-IR and UV radiation
  • Laser light in machine vision
  • Use of strobe lighting in machine vision
  • Placement of sources
  • Effect of stray/ambient light
  • Filters and their use
  • Optical devices for image enhancement

MODULE 5: CAMERAS AND SENSORS

  • CMOS and CCD sensors
  • CCPD arrays
  • Colour vs. monochrome applications
  • Charge transfer devices and charge injection device
  • 3D sensing applications
  • Sensor positioning
  • Sensors for difficult environments
  • Speed vs. resolution
  • Types of cameras
  • Camera viewpoint
  • Field of view
  • Resolution evaluation
  • Selection of a lens

MODULE 6: IMAGE PROCESSING

  • Real time processing
  • Precision and accuracy
  • Selection of frame grabber/vision appliance
  • Frame grabbing
  • Use of multiplexing
  • IEEE 1394 'firewire' serial bus standard interface
  • Basic approach of image representation and processing software applications
  • Interactive image processing for system prototyping
  • High speed versus real time approaches
  • Selection of software packages

MODULE 7: IMAGE ANALYSIS

  • Common algorithms
  • Enhancing the image
  • Blob analysis
  • Pattern matching
  • Optical character recognition
  • Read bar codes and data matrix
  • Perform measurements
  • Overlay graphics

MODULE 8: LOW-LEVEL VISION

  • Basic image filtering operations
  • Thresholding techniques
  • Edge detection
  • Corner and interest point detection
  • Mathematical morphology
  • Texture

MODULE 9: INTERMEDIATE-LEVEL VISION

  • Binary shape analysis
  • Boundary pattern analysis
  • Line detection
  • Circle and ellipse detection
  • The Hough transform

MODULE 10: EXTERNAL INTERFACE

  • Function of external interface
  • Object presentation
  • Physical tolerances
  • Handling special objects
  • Actions after image processing
  • Interfacing through programmable logic interface
  • Interfacing machine vision with industrial robots
  • Industrial challenges – heat/cold/vibration/ EMI/EMC issues

MODULE 11: CONSTRUCTING A MACHINE VISION SYSTEM

  • Selecting an application for machine vision implementation
  • Perceived value addition
  • Cost justification
  • Alteration in process line
  • Building a system with off-the-shelf components
  • Integration requirements
  • Buying turn-key solutions
  • Obsolescence and expandability issues
  • Budgeting

MODULE 12: TYPICAL APPLICATIONS

  • Application profiles
  • Component inspection
  • Pharma applications
  • Packaging applications
  • Road inspection using vehicle mounted sensors
  • 3D application examples

 

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How can an e-learning course be interactive?

Boredom can be a real danger, however, we use an interactive approach to our e-Learning – with live sessions instead of recordings.  The webinar software allows everyone to interact and involves participants in group work; including hands-on exercises with simulation software and remote laboratories where possible.  You can communicate with text messages, or live VoIP speech, or can even draw on the whiteboard during the sessions.

 

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