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Course Overview

This course will cover the application of machine vision and pattern recognition technologies in Advanced Manufacturing. Participants would be instilled with the essential knowledge of machine vision systems including their key components, functionality and the image processing technologies. On top of that, the course will also provide an overview of the techniques in image analysis and the derivation of useful hidden patterns in the images. These would include the selection, development and application of suitable pattern recognition techniques in solving a given problem.

Entry Requirements

Participants should have relevant working experiences in manufacturing sector.

Who Should Attend

Engineers, Technology Specialist

What You'll Learn

Day 1

9.00 am – 12.00 pm

Describe the key concepts of machine vision systems

  • Explain the goals of machine vision systems in factory automation
  • Describe the main components of machine vision systems according to the working environment and requirements
  • Describe the various lighting systems used in machine vision systems
  • Distinguish between image processing and image analysis
  • Define the terminologies of image formation and focusing


12.00 am – 1.00 pm

Lunch Break


1.00 pm – 5.00 pm

Comprehend the fundamentals of image processing techniques used in machine vision systems

  • Explain the properties of images for processing
  • Distinguish between frequency and spatial domains
  • Describe the concept of Fourier Transformation in imagine processing
  • Define the histogram and threshold methods used in image processing
  • Describe the convolution mask method in image enhancement, noise reduction, filtering and connectivity
  • Describe segmentation by region growing and region splitting
  • Define morphology operations in image processing



Day 2

9.00 am – 12.00 pm

Apply image analysis techniques in machine vision systems

  • Describe elementary object recognition and identification by features
  • Compare scene analysis and mapping
  • Apply the detection and localization of edges
  • Describe stereo imaging techniques in machine vision system
  • Describe specialized lighting techniques in depth measurement


12.00 am – 1.00 pm

Lunch Break


1.00 pm – 5.00 pm

Apply Pattern Recognition in the domain of Machine Vision and in a manufacturing setting

  • Explain Pattern Recognition as a class of Machine Learning
  • Apply a software platform for Pattern Recognition
  • Perform image formation and preprocessing
  • Apply feature extraction from images
  • Apply labelled data and unlabelled data in the design of Pattern Recognition systems for Machine Vision via supervised learning and unsupervised learning
  • Apply Pattern Recognition concepts to develop simple Machine Vision Automation Systems



Day 3

9.00 pm – 12.00 pm

Analyse machine vision examples using Regression, Clustering and Classification

  • Analyse a Machine Vision problem using the Regression, Clustering and Classification techniques
  • Apply Pattern Recognition techniques to a Machine Vision model


12.00 am – 1.00 pm

Lunch Break


1.00 pm – 5.00 pm

Analyse machine vision examples using Regression, Clustering and Classification (Continue)

  • Compare the performance of the pattern recognition techniques for the given Machine Vision problem
  • Analyse the results and suggest possible improvements



Day 4

9.00 pm – 12.00 pm

Develop a machine vision and pattern recognition application

  • Identify the appropriate applications for vision guided factory automation
  • Perform the setting up of a machine vision system to acquire an image


12.00 am – 1.00 pm

Lunch Break


1.00 pm – 5.00 pm

Develop a machine vision and pattern recognition application (Continue)

  • Set the boundary conditions of machine vision system for industrial automation
  • Develop a machine vision and pattern recognition manufacturing application

Written Assessment (Open Book)





Participants will be issued with a Certificate of Accomplishment upon meeting 75% of the required course attendance.

Course Schedule/Apply

Intake Info Application Closing Date Course Duration

04 - 05 April 2023

04 March 2023

2 days & 16 hours self-pace e-learning

9.00am - 5.00pm


Registration may be closed earlier due to overwhelming response.


For Corporate training, click here.

Course Fees

Fees Type Course Fees
(w GST) 
Singapore Citizens
Full Course Fee / Repeat Students S$1,284.00
Aged 40 and above / SME-sponsored S$145.20
Aged below 40 S$385.20
Non-Singapore Citizens
Full Course Fee / Repeat Students S$1,296.00
Singapore Permanent Residents / Long-Term Visit Pass Plus (LTVP+) Holder S$388.80
SME-sponsored (Singapore Permanent Residents) / Long-Term Visit Pass Plus (LTVP+) Holder) S$148.80

SkillsFuture Credit Approved. For more details, please click here

With effect from 1 Jul 2020, the Workforce Training Scheme (WTS) will be replaced by the Work Support Scheme (WSS), for more information, please visit:

Lecturer/Trainer Profile

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Course Contact

  • 67881212
  • Monday - Thursday: 8:30am - 6:00pm
    Friday: 8:30am - 5:30pm
    Closed during lunchtime, 12:00pm - 1:00pm
    and on weekends and public holidays.

  • https://www.tp.edu.sg/tsa
  • Temasek SkillsFuture Academy
    Temasek Polytechnic
    East Wing Block 1A,
    Level 3, Unit 81
    21 Tampines Ave 1
    Singapore 529757


  • Temasek Polytechnic reserves the right to alter the course, modify the scale of fee, amend any other information or cancel a course with low enrolment.

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