[Free] Learn Computer Vision (For Beginners) Part 2

Boundary-Handling Padding Image Processing Edge Detection Gaussian Laplacian Principal Component Analysis Filtering – Free Course

Added on March 24, 2025 IT & Software 2 min read

What you’ll learn

• Master Image Filtering & Edge Detection
• Enhance Images with Pyramids & Morphology
• Apply Template Matching & Feature Extraction
• Perform Dimensionality Reduction for Images

Requirements

• Learn Computer Vision (for Beginners) Part 1

Description

Learn Computer Vision (for Beginners) Part 2

Master essential image processing techniques and build a strong foundation in Computer Vision!

Are you ready to take your Computer Vision skills to the next level? This course is designed for beginners who want to dive deeper into image processing, feature extraction, and recognition techniques. Through interactive lessons and hands-on coding exercises, you will develop a solid understanding of key concepts and algorithms used in modern Computer Vision.

What You Will Learn:

Fundamentals of Image Processing

• Understanding Linear Filtering and how it transforms images

• Applying Convolution Kernels for edge detection and smoothing

• Implementing Separable Filters for efficient computations

• Exploring different Boundary Handling techniques

Noise Reduction & Image Transformations

• Gaussian Pyramid & Aliasing: Multiscale image representation

• Median Filter & Morphology: Techniques to remove noise and enhance structures

Edge Detection & Feature Extraction

• Understanding and implementing the Canny Edge Detector

• Non-Maximum Suppression for refined edges

• Laplacian & Laplacian Pyramid for feature enhancement

Template-Based Recognition & Matching

• Template Matching and its applications

• SSD (Sum of Squared Differences) and Correlation techniques

Dimensionality Reduction & Subspaces

• Introduction to PCA (Principal Component Analysis) and SVD (Singular Value Decomposition)

• Understanding how reducing dimensions helps in feature extraction

Hands-on Coding Implementation

• Code for Canny Edge Detection & Image Pyramids

• Practical exercises to apply learned concepts

Who Is This Course For?

• Students and professionals looking to expand their Computer Vision knowledge

• Beginners who have a basic understanding of Python and want to implement image processing techniques

• AI and Machine Learning enthusiasts curious about feature extraction and image recognition

By the end of this course, you will have built a strong intuition for image transformations, edge detection, and pattern recognition, giving you a solid foundation for advanced topics like deep learning in Computer Vision.

Enroll now and start your journey in Computer Vision today!

Author(s): Kaivalya GeetaPutri