Image Processing (521H3)
15 credits, Level 7 (Masters)
Spring teaching
This module introduces you to advanced image processing and computer vision topics. Computer vision is increasingly used as a powerful method to enable computers to understand the world around them. It has applications in many areas including autonomous factory production, security, biomedical imaging, autonomous vehicles and robotics.
This module will introduce the concepts, starting with basic operations and finish with state-of-the-art deep learning architectures that enable computers to identify, track and understand objects in the real world.
Capturing a good quality image is an important first step, so you’ll learn about the lens optics, camera technology and noise removal processes. You’ll then cover medium-level processes such as edge detection, segmentation, blob analysis and colour processing. Once these have been mastered you’ll study the higher-level subjects such pattern matching, key point descriptors and deep learning convolutional neural networks.
Topics include:
- an introduction to image processing and elements of computer vision
- camera technologies, lenses for machine vision, image formation and resolution
- de-noising images
- histogram manipulations
- linear invariant systems in two dimensions, the discrete convolution operator
- first- and second-order differential edge detection operators, edge-filling techniques
- the Hough transform
- scene segmentation methods and morphological operators
- colour transforms
- pattern recognition techniques: shape descri