Image Processing

Description

This course represents one of the main goals of the ExpoTec journey: moving students from machines that simply follow programmed instructions to machines capable of understanding information from their environment.

Students begin by understanding how computers represent and process digital images.

Using Python and OpenCV, they learn how to capture images and video from cameras, manipulate images, extract useful information, identify shapes and colors, track objects, and detect visual features.

They then progress into more advanced Computer Vision applications and are introduced to AI-based visual recognition and detection.

Students use pre-trained AI models and appropriate libraries to enable their Raspberry Pi systems to recognize and detect objects from camera input.

Most importantly, students connect Computer Vision back to the physical engineering systems they have built throughout ExpoTec.

A camera is no longer simply used to display video.

It becomes a sensor capable of providing rich information to a machine.

The system can:

See → Process → Understand → Decide → Act

This allows students to begin developing intelligent robots and machines that react to visual information from the real world.

Learning Objectives

By the end of the course, students will be able to:

• Understand how digital images are represented by computers.
• Understand Pixels, Resolution, and Color Channels.
• Capture images and video using cameras.
• Use OpenCV with Python.
• Read, display, resize, crop, and transform images.
• Work with RGB, Grayscale, and other image representations.
• Apply basic Image Filtering.
• Understand Thresholding.
• Detect basic shapes and visual features.
• Perform Color Detection.
• Understand Contours.
• Track objects through video.
• Process real-time camera streams.
• Understand the difference between traditional Image Processing and AI-based Computer Vision.
• Understand the basic concept of Machine Learning.
• Understand the basic concept of Neural Networks at an introductory level.
• Use Pre-Trained AI Models.
• Perform basic Object Detection.
• Process detection results programmatically.
• Connect visual detection results to physical machine behavior.
• Build Raspberry Pi-based Computer Vision applications.
• Integrate Cameras + Python + AI + Electronics + Robotics into intelligent systems.