Real Time Computer Vision on Embedded System
Duration – 3 Days
Objectives
• Understand core concepts of image processing such as
filtering, edge detection, and segmentation using
OpenCV.
• Gain hands-on experience with real-time image
processing tasks on Raspberry Pi using Python.
• Build simple real-time applications such as object
detection and motion tracking.
• Bridge theory with practical skills for applying
computer vision in IoT and edge computing projects
Tools & Platforms
- • Raspberry pi+micro-USBcable
• Internet connectivity
• USB keyboard and mouse
• Windows 7(or higher) system to download Micro
Python
Pre-requisites
• Basic programming and Hardware knowledge
• Basic knowledge of Python
• Basic knowledge of Microcontrollers
• Basic knowledge of Linu
Take away
• Practical skills in OpenCV for image processing.
• Real-time vision application development on
Raspberry Pi.
• Hands-on with filters, edge detection,
and segmentation.
• Understanding of embedded computer
vision workflows.
• Ready-to-use code templates for future projects
Session 2: Image Segmentation Techniques
• Introduction to Segmentation
• Thresholding (Global, Adaptive)
• Color Space Conversion (RGB → HSV,
• Grayscale)
• Morphological Operations
• Dilation, Erosion, Opening, Closing
• Contour Detection & Object Counting
• Count objects using contours
• Performance considerations: Optimization tips for Pi
Session 2: Real-Time Computer Vision on Embedded Devices
• What is Embedded Vision?
• Why Raspberry Pi for Edge AI
• Raspberry Pi Camera Module Setup
• OpenCV installation on Raspberry
• Demo Session On these
