Automatic Vectorization: Principles and Applications

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Related lectures (26)

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Image Processing in Python: Manipulation and Convolution Techniques

Introduces image processing techniques in Python, focusing on manipulation and convolution operations using NumPy and Pillow.

Vector-Vector Integration: Methods and Tools

Explores methods and tools for integrating vector layers in QGIS, including SQL queries and boolean operators.

Image Processing I: Edge Detection and Texture Analysis

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

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.

Image Processing I: Correlation Measures and Matched Filtering

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

Digitization of Vector Objects

Covers the digitization of vector objects in GIS, including creation, editing, and topology management.

Edge Detection: Deep Learning Insights

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

Projective Geometry: Anharmonic Cross Ratio and Conics

Explores anharmonic cross ratio, projective geometry birth, and practical applications.

Deep Learning: Edge Detection and Neural Networks

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

Directional Image Analysis: Steerable Filters

Explores directional image analysis and the implementation of steerable filters for edge and ridge detection.