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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.



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