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Lecture
Edge Detection: Basics
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Related lectures (25)
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Image Filtering: Classic Filters
Explores classic image filters like Moving Average, Gaussian Blur, Sobel filter, and Laplacian operator.
Image Processing Basics
Introduces image processing basics in Python, covering manipulation, grayscale conversion, edge detection, and convolution with kernels.
Delineation: Techniques and Applications
Explores techniques for delineation, including Hough transform, gradient orientation, and shape detection, emphasizing the importance of combining graph-based techniques and machine learning.
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 in Python: Manipulation and Convolution Techniques
Introduces image processing techniques in Python, focusing on manipulation and convolution operations using NumPy and Pillow.
Automatic Vectorization: Principles and Applications
Covers the potential and limits of automatic vectorization techniques for digitizing objects from scanned documents or images.
Ground Penetrating Radar: Data Analysis
Explores the automated picking of reinforcement bars within Ground Penetrating Radar data using machine learning and signal processing techniques.
Image Processing I: Discrete Histogram Processing and Spatial Operators
Explores discrete histogram processing and spatial operators for image manipulation and noise reduction.
Reconstructing Color Images: Techniques and Applications
Covers techniques for reconstructing color images using optical detection and artificial intelligence to enhance image quality and reduce noise.
Probability Distributions in Environmental Studies
Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.
