Training workshop on

IMAGE PROCESSING USING OPENCV-PYTHON

(Basics to Applications)

(HRD Corp claimable - SBL Khas 10001452456)

[Total number of engineers trained to date: 8]

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"Very detailed and very easy for a beginner to build their foundation on this knowledge"

- comment from past participant (see more below)​
 

(In-house training available. Please contact trainer)

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Course summary

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Image processing is the central element in all machine vision systems. In this hands-on online workshop, the participants will be guided into understanding the various image processing operations using OpenCV and Python, such as enhancing images, suppressing noise, detecting edges, performing segmentation and morphological operations, as well as extracting information from objects within the images for the purpose of classification and decision making. The theory behind some of the more advanced image processing operations, such as contrast stretching, histogram equalization, gamma correction, Gaussian filtering, median filtering, adaptive thresholding, grayscale dilation and erosion, etc. will be explained to the participants. The participants will learn how to apply the knowledge gained in the workshop to solve some real-life problems, such as detecting missing components in printed circuit boards, detecting broken cookies, counting total value of coins, counting the number of colored pins, reading resister color code etc.

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How will I benefit?

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• Learn to write OpenCV-Python codes to crop & resize image, enhance image contrast, extract color planes, suppress noise, detect edges, perform segmentation, extract object properties, and perform simple rule-based classification.

• Understand the theory behind some of the advanced image processing operations, such as histogram equalization, gamma correction, Gaussian filtering, median filtering, adaptive thresholding, grayscale dilation and erosion 

• Solve real-life machine vision problems using OpenCV-Python, such as detecting missing components on PCB, detecting and locating defects on photomask, detecting wafer imprinting defect, measuring diameter of pin gauge, detecting broken cookies, counting total value of Malaysian coins, counting number of colored objects etc. 

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Course content

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Day 1 (Basics)

 

Installing OpenCV & Python

Reading & displaying images using OpenCV

Extracting pixel information & color planes

Extracting image dimensions to variables

Manipulating images: resizing, rotating, cropping

Creating image from an array

Displaying image with pixel location and value

Displaying multiple images within same window

Adding & subtracting images

Displaying and interpreting image histograms

Enhancing images (contrast stretching, histogram equalization, gamma correction)

Plotting intensity profile across image

Filtering operations (Average, median, Gaussian etc.)

Morphological operations (Grayscale and binary dilations and erosions)

Detecting edges using various edge operators (Sobel, Canny, Prewitt, Hough transform)

Segmenting images (global, adaptive, Otsu's thresholding)

Extracting region properties (area, centroid, bounding box)

Activities (see activity sheets)

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Day 2 (Applications - activity based)

 

Detecting missing components & defects on a PCB (see activity sheet)

Detecting broken or damaged cookies (see activity sheet)

Counting total value of Malaysian coins (see activity sheet)

Measuring diameter of pin gauge (see activity sheet)

Detecting and locating wafer imprinting defect (see activity sheet)

Counting number of colored pins of specific color (see activity sheet)

​Reading resistor color code (see activity sheet)

 

Course duration

14 hours (over two days)

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Mode of delivery

Face-to-face

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Trainer fee

Please contact trainer for quotation.

 

Who should attend

Anyone new to OpenCV-Python or interested to learn the basics of image processing using OpenCV-Python as well as solve practical machine vision problems.

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