[Free] Learn Computer Vision (For Beginners) Part 2
Boundary-Handling Padding Image Processing Edge Detection Gaussian Laplacian Principal Component Analysis Filtering – Free Course
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
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Understanding Linear Filtering and how it transforms images
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Applying Convolution Kernels for edge detection and smoothing
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Implementing Separable Filters for efficient computations
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Exploring different Boundary Handling techniques
Noise Reduction & Image Transformations
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Gaussian Pyramid & Aliasing: Multiscale image representation
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Median Filter & Morphology: Techniques to remove noise and enhance structures
Edge Detection & Feature Extraction
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Understanding and implementing the Canny Edge Detector
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Non-Maximum Suppression for refined edges
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Laplacian & Laplacian Pyramid for feature enhancement
Template-Based Recognition & Matching
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Template Matching and its applications
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SSD (Sum of Squared Differences) and Correlation techniques
Dimensionality Reduction & Subspaces
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Introduction to PCA (Principal Component Analysis) and SVD (Singular Value Decomposition)
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Understanding how reducing dimensions helps in feature extraction
Hands-on Coding Implementation
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Code for Canny Edge Detection & Image Pyramids
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Practical exercises to apply learned concepts
Who Is This Course For?
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Students and professionals looking to expand their Computer Vision knowledge
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Beginners who have a basic understanding of Python and want to implement image processing techniques
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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
