Industrial Machine Vision
& Image Processing
Course
1. Course Objectives
This course aims to give participants
a good foundation in image processing theory as well as the ability
to apply this knowledge to the design and implementation of systems
for machine vision in the real world. Components of machine vision
systems that are currently available in the market will be
discussed. There will also be hands-on sessions to perform simple
machine vision tasks on an integrated system. The course will also
touch on the trends evident in the machine vision industry with the
advent of technological advances in processing power and higher
transistor density.
2. Course Outline
Day 1:
Overview of Machine
Vision
·
What it is and what it is not
·
Typical tasks - Bar Code & Data Matrix
identification, Precision Gauging, Presence Verification, Print
Quality Inspection, Optical Character Recognition (OCR)
Theory of Image
Processing
·
Terminology - Pixel, Image, Filter, Frame Rate,
Histogram
·
Gray Scale Transformations - Look-up Tables, Histogram
Equalization
·
Image Arithmetic - Addition, Subtraction, Minimum
& Maximum
·
Spatial Linear Filters - Averaging, Smoothing, Edge
Detection
·
Spatial Statistical Filters - Median Filters
·
Morphological Filters
·
Identification - Classification, Template Matching
Components of Machine
Vision System
·
Optical Lenses - Telecentric, Microscopic,
Telephoto
·
Analog & Digital Cameras - interlaced,
progressive, area, line, CCD, CMOS, TV standards (PAL, NTSC)
·
Digital and Analog Frame grabbers
·
Machine Vision Software - Application, Image
Processing Library, Hardware SDK
·
Lighting - Fluorescent, Fiber-Optics, LEDs
·
Interface with other machines - Digital I/O, RS-232,
Customized Communications
Day 2:
Choosing Sensor and
Lens
·
Video Formats
·
Object Distance, Working Distance - Choosing the
correct Lens
·
Types of Lens Mounts - C, CS, F bayonet
System Resolution &
Achievable Accuracy
·
Sensor size
·
Optical Magnification
·
Pixel Resolution
·
System Accuracy
·
Example 1: Configuring an Area Scan System
·
Example 2: Configuring a Line Scan System
Playing with
Lighting
·
Backlight
·
Frontlight
·
Diffused Light
·
Coaxial Illumination
Common Software
Algorithms
·
Image Filtering
·
Image Arithmetic
·
Positioning
·
Classification
Day 3:
Hands On Practicum
·
Practical 1: Presence Verification
·
Practical 2: Positioning Alignment
·
Practical 3: Gauging Measurement
·
Practical 4: Pattern Recognition using Machine
Learning
·
Practical 5: Pattern Recognition using Template
Matching
Industry Outlook
·
Camera Link Standard for Digital Cameras
·
High Resolution Sensors with Higher Frame-Rates
·
Smart Cameras
·
Image Data Archiving - High Speed Logging
·
Newer Algorithms - Alignment
·
Frame grabbers with on-board Processors - DSPs,
FPGAs
3. Course Details
The maximum enrollment per class is 4
delegates. Course materials and a book entitled “Industrial Image
Processing - Visual Quality Control in Manufacturing” by C. Demant
et alii will be given to each delegate for post-course
reference.
Venue:
Neurotech Pte Ltd.
Time:
10:00am to 5:30pm for a total of 3 days
Fee:
Call
Discount:
2nd pax and follows enjoy 5% discount.
