Directional Image Analysis: Steerable Filters

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Directional Image Analysis and Processing

Delves into the mathematical foundations and importance of directional cues in image processing, exploring computational challenges and selectivity to orientation.

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Covers the basics of computer vision, focusing on image processing techniques and feature detection.

Edge and Contour

Covers edge and contour detection in images, including gradient-based methods, Laplacian operator, and more complex methods.

Edge Detection: Deep Learning Insights

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Image Processing I: Correlation Measures and Matched Filtering

Explores correlation measures, matched filtering, and feature extraction in image processing.

Deep Learning: Edge Detection and Neural Networks

Discusses edge detection techniques and the evolution of deep learning in neural networks.

Topology: Polyhedral Products and Edge Detection

Explores topology concepts and edge detection in computer vision, highlighting the significance of contours and gradients in image analysis.

Image Processing: Neighborhood Averaging & Gaussian Smoothing

Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.

Image Processing I: Edge Detection and Texture Analysis

Covers edge detection, texture analysis, Canny's algorithm, filterbanks, and segmentation techniques.

Edge Detection: Basics

Covers the basics of edge detection, including edge duality, discontinuities, descriptors, gradients, and magnitude measurement.