Explore the Hough Transform and its applications in image processing through this 43-minute lecture from the University of Central Florida. Delve into image feature extraction techniques, focusing on shape features and line fitting methods. Learn about least squares fit, line fitting segmentation, and the Hough Transform's polar form equation. Examine image gradients, line fitting examples, and the impact of noise factors. Investigate practical circle fitting techniques and the Generalized Hough Transform. Discover how to generate R-tables for shape detection and achieve rotation and scale invariance in image analysis.
Overview
Syllabus
Image Feature Extraction
Shape Features
How to Fit A Line?
Least Squares Fit
Line Fitting: Segmentation
Line Fitting: Hough Transform
Polar Form of Equation of Line
Image Gradient
Line Fitting Examples
Noise Factor
Difficulties
More Practical Circle Fitting
Generalized Hough Transform
Generating R-table
Detecting shape
Rotation and Scale Invariance
Taught by
UCF CRCV
