Module 02523 (2002)
Syllabus page 2002/2003
06-02523
Image Understanding
Level 3/H
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
hipr
(HyperMedia Image Processing Reference) is a web-based
resource covering many topics relevant to this module.
CVonline
A growing collection of articles on the state-of-the-art
methods in computer vision,
written by experts in the field.
Other information. This link will be updated as the
module progresses.
Outline
Visual systems; Visual processing -natural & computational solutions (image formation, image enhancement, early vision and detection of visual primitives, grouping and segmentation, surface and object formation); Image and object representation; feature extraction and description (colour, tone and texture, geometric features, shape); Object recognition; Case studies; Current research.
Aims
The aims of this module are to:
- introduce concepts and methodologies for digital image processing, analysis and computer vision, including necessary foundations in mathematics, digital signal processing, statistics and human visual perception
- develop skills in appropriately chosing computational tools and techniques for constructing computer systems for image processing and analysis
- gain appreciation of current research problems in selected areas of image analysis and computer vision
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | follow textbooks and basic research articles on image analysis and computer vision | Examination |
| 2 | understand the relevant theoretical concepts underlying the vision algorithms from the fields of mathematics, digital signal processing and statistics | Examination |
| 3 | design basic image processing algorithms and systems for solving simple image analysis problems | Examination |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
Conventional lectures, 2 hrs lectures per week.
Practical exercises in image processing and analysis (not assessed)
and directed reading, individual study hours.
Web-based material (hipr) for individual study.
Contact Hours:
Assessment
- Supplementary (where allowed): As the sessional assessment
- 2 hr examination (100%).
Recommended Books
| Title | Author(s) | Publisher, Date |
| Image Processing, Analysis and Machine Vision | Sonka M, Hlavac V & Boyle R | 1999 |
| Visual Perception | V Bruce, P R Green & M A Georgeson | 1997 |
Detailed Syllabus
-
Visual systems (1 lecture)
- Taxonomy
- Visual systems in nature
- Visual processing - natural & computational solutions
(10 lectures)
- Image formation
- Image enhancement
- Early vision & detection of visual primitives
- Grouping and segmentation
- Surface and object formation: stereo vision, surface shape from shading & texture
- Image and object representation; feature extraction
and description (3 lectures)
- Colour, tone and texture
- Geometric features
- Shape
- Object recognition (2 lectures)
- Computational representations
- Models and model matching
- Case studies in image analysis (2 lectures)
- Current research - selected topics (2 lectures)
Last updated: 29 July 2001
Source file: /internal/modules/COMSCI/2002/xml/02523.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus