COMPGV11 - Geometry of Images

This database contains the 2016-17 versions of syllabuses. Syllabuses from the 2015-16 session are available here.

Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).

Code COMPGV11 (Also taught as: COMPM081)
Year MSc
Prerequisites N/A
Term 2
Taught By Simon Arridge (50%)
Lewis Griffin (50%)
Aims To introduce the generalisation of image processing to n-Dimensional data : volume data, scale space, time-series and vectorial data.
Learning Outcomes To understand the principles of image processing in n-dimensions, time-series analysis and scale space, and to understand the relations between geometric objects and sampled images.


0. Basic Image Operations
Fourier Transforms
Convolution and Differentiation in Fourier Domain Recursive Filters
Marching Square/Cubes
Level Set Methods

1. Introduction to Differential Geometry
1.1 Images as functions
- Definitions
- Taylor Series expansion and the Koenderick jet
- Properties of the local Hessian
- Definition of extrema and saddle points
- Ridges in n-di