Computer Vision with Raspberry Pi

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A Quick Prototype Approach with Scilab!

Learning Computer Vision with Scilab in Pi is Much Easier! 

 


 “Learning Computer Vision with Scilab in Pi is Much Easier!”

 

Course Synopsis

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Raspberry Pi has become a hot topic for researchers and hobbyists in various fields due to its wide usage. While Python/C++ has becoming the common programming languages for Pi development, other high level languages are able to find their place with the Pi as its processing ability is getting more powerful.

 

Cousrse Objectives

This course introduces the Raspberry Pi as a platform for Computer Vision with Scilab - The Open Source Numerical Software which has been widely used in many platforms for research and development. Some prominent use case for Scilab can be found at http://scilab.io/.

Taking the advantage of Scilab able to integrate with other languages, we develop a module to utilize the power of OpenCV but with the easy-to-learn Scilab syntax.

 

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Who Must Attend

This course is suitable for participants who would like to embrace Computer Vision by using the Raspberry Pi as the platform.

Prerequisites

Participants should have basic background in programming and electronics

 

Course Methodology

This course is presented in a workshop style with example-led lectures interlaced with demonstrations and hands-on practical for maximum understanding.

 


Course Outline

  • Introduction
    • Overview of Raspberry Pi
    • Overview of Scilab
    • RaspPi + Scilab + OpenCV for Computer Vision
    • How Pi Sees images
  • Working with Images
    • Importing image from pictures
    • Acquiring image from usb webcam
    • Viewing the acquired image
    • Image pixel and its' values
    • Converting image between Data Classes and Image Types
  • Fundamental of Image Processing
    • Converting Colour to Grayscale
    • Adjusting image intensity
    • Enhancing images using arithmetic operations
    • Correcting image alignment
    • Cropping and resizing images
    • Converting Grayscale to Binary
  • Filtering Images
    • Image convolution and correlation
    • Spatial domain filtering
    • Frequency domain filtering
  • Feature Extraction
    • Image thresholding
    • Edge detection
    • Radon transform
    • Morphological segmentation
  • Color-based Image Processing
    • Procesing RGB Images
    • Color space conversion
  • RaspPi GPIO from Scilab
    • Control GPIO on Raspberry Pi with Scilab
  • Mini Project 1 - Objects Counting
    • Counting preferred objects
  • Mini Project 2 - Motion Detection
    • Object existence detection
  • Mini Project 3 - Machines Learning
    • Object identification with neural network
    • Decision making and controlling external devices

 

To obtain details of the course (fee, location and etc.), kindly obtain a registration form by email tina@tritytech.com

Provide us with your name, organization & mobile contact number.

You may also call us at +603-80637737 or fill up our Training Enquiry form.

 

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