Course at a Glance

Schedule

Code: CMV
Course Length: 3 Months

In this interactive 3 month 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

 

Course Details

Overview

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.


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
 

Learning and Teaching

Benefits of eLearning to Students

  • Cost effective: no travel or accommodation necessary
  • Interactive: live, interactive sessions let you communicate with your instructor and fellow students
  • Flexible: short interactive sessions over the Internet which you can attend from your home or office. Learn while you earn!
  • Practical: perform exercises by remotely accessing our labs and simulation software
  • Expert instructors: instructors have extensive industry experience; they are not just 'academics'
  • No geographical limits: learn from any location, all you need is an Internet connection
  • Constant support: from your instructor(s) and a dedicated Learning Support Officer for the complete duration of the course
  • International insight: interact and network with participants from around the globe and gain valuable insight into international practice 


Benefits of eLearning to Employers

  • Lower training costs: no travel or accommodation necessary
  • Less downtime: short webinars (60-90 minutes) and flexible training methods means less time away from work
  • Retain employees: keep staff who may be considering a qualification as full time study
  • Increase efficiency: improve your engineering or technical employees’ skills and knowledge
  • International insight: students will have access to internationally based professional instructors and students

 

How Does it Work?

EIT eLearning courses involve a combination of live, interactive sessions over the Internet with a professional instructor, set readings, and assignments. The courses include simulation software and remote laboratory applications to let you put theory to practice, and provide you with constant support from a dedicated Learning Support Officer.


Practical Exercises and Remote Laboratories

As part of the groundbreaking new way of teaching, our online engineering courses use a series of remote laboratories (labs) and simulation software, to facilitate your learning and to test the knowledge you gain during your course. These involve complete working labs set up at various locations of the world into which you will be able to log to and proceed through the various practical sessions.

These will be supplemented by simulation software, running either remotely or on your computer, to ensure you gain the requisite hands-on experience. No one can learn much solely from lectures, the labs and simulation software are designed to increase the absorption of the materials and to give you a practical orientation of the learning experience. All this will give you a solid, practical exposure to the key principles covered and will ensure that you obtain maximum benefit from your course.

 

Endorsed by ISA

School of Industrial Automation