COMP27112 Computer Graphics and Image Processing syllabus 2019-2020
Visual Computing brings together two fundamentally important aspects of modern computing: Computer Graphics - concerned with the synthesis of images from computer models - and Image Processing, which deals with analysis and understanding of images by computers. There are now considerable overlaps between these two, traditionally separate, fields of research and their applications.
The Visual Computing theme consists of the following course units:
- Year 2: Computer Graphics and Image Processing (10 credits)
- Year 3: Advanced Computer Graphics (10 credits)
- Year 3: Computer Vision (10 credits)
The importance of visual interfaces has never been greater. Graphical interfaces have become ubiquitous, from desk-top interaction, to games and three-dimensional virtual environments. In parallel, there has been an explosion in digital image processing and analysis. We take for granted digital photography and video, while our health services rely on digital X-ray systems, CT and MRI scanners for seeing inside our bodies. Meanwhile, the visualization of computer simulations is an essential aspect of product design and testing, genome exploration, drug design, and climate modelling. The demand for computer scientists with advanced knowledge of such areas has never been greater.
The theme will enhance your knowledge and understanding, answering such questions as:
- How are three-dimensional environments represented in a computer, and how are interactive 3D worlds created?
- How are 2D and 3D representations combined ? for example, how can we recover 3D geometry from 2D images?
- How are the basic mathematical techniques and algorithms used to build useful applications?
- How are images stored, processed and manipulated?
- How can computers interpret images captured by cameras and other recording devices?
Fundamentals (1 week)
2 and 3 D Coordinate systems. Vectors, matrices and basic vector/matrix operations.2 and 3 D geometric transformations (translation, rotation, scaling, affine).
3D Modelling and Illumination (5 weeks)
The camera model. Viewing and projection. Points, lines, B?zier curves. Polygons. Local illumination: ambient, diffuse and specular components. Interpolation: intensity (Gouraud) and normal vector (Phong). Surface detail: textures, bump mapping. Model structuring using scene graphs. Masters and instances. Inheritance of transformations and attributes.
OpenGL (in C) laboratory exercises. Self-paced Coursework Assignments using example programs and software tools (with a small amount of experiment-driven programming).
Image Transformations (2 weeks)
Pixels, pixel values, grey level, spatial resolution, colour representations, image transformations: point transformations (windowing, histogram equalisation, colour transformations ? colour spaces).
C Programming, manipulating images using C, low level image processing.
Image Enhancement (3 weeks)
Local processes, convolution, image smoothing (local averaging, weighted averaging), size of support, Gaussian mask. Edge enhancement (unsharp masking). Edge detection (Prewitt, Sobel, Canny), Thresholding, blob detection, simple measurement (geometric features). Rank order filters (median, max-min).
MATLAB exercises in image processing. Noise reduction. General image convolution code. Using the code to make an edge detector (Sobel, Prewitt), Combined smoothing and edge detection ? Scale.
24 hours spread over 12 weeks
5 hours of assessed, self-study Coursework Assignments.
10 hours in total, 5 2-hour sessions.
Feedback methodsFace to face feedback and marking in programming laboratories.
- Assessment written exam (2 hours)
- Lectures (24 hours)
- Practical classes & workshops (10 hours)
- Analytical skills
- Project management
- Problem solving
On successful completion of this unit, a student will be able to:
- Describe the principles of interactive computer graphics
- Design systems using fixed-pipeline OpenGL
- Apply the mathematics of 3D transformations and viewing
- Describe the principles of the rendering pipeline
- Describe the principles of image processing
- Implement fundamental image processing algorithms
No reading list found for COMP27112.
Course unit materials
Links to course unit teaching materials can be found on the School of Computer Science website for current students.