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Computer Vision/Digital Image Processing (Forår 2010)

Kursuskode : EDIP-U1
ECTS Point : 7,5 Status : Tilvalg
Revideret : 06/02 2010 Oprettet : 07/01 2005
Placering : 5-7 semester Timer pr. uge : 4
Længde : 1 semester Undervisningssprog : Dansk hvis der ikke er engelsksprogede studerende tilstede

Målsætning : Digital imaging, video and related processing have experienced exceptional growth in recent years and have become prevalent in a wide variety of applications: Consumer, industrial, military as well as scientific markets. With the study module the student will learn and apply fundamental concepts and techniques of digital image processing to typical applications such as: automatic image enhancement, object inspection and flaw detection, object classification/recognition and image data compression/decompression.

Specifically the student will:
- Acquire knowledge of image sources, acquisition techniques and digital representation of images
- Acquire knowledge of human light and colour perception
- Be able to analyse images in the spatial or frequency domains and subsequently apply automatic processing for image enhancement
- Be able to apply pseudo-colour or full colour processing
- Comprehend and apply techniques for edge detection and linking in computer automated object classification/recognition
- Comprehend and apply methods for compression/decompression of images
- Design and test processing algorithms with MATLAB’s image processing toolbox.
Hovedindhold : Image sources and image acquisition
Image representation
Human visual perception
Image enhancement in the spatial domain
Image enhancement in the frequency domain
Image restoration
Color image processing
Image compression/decompression
Image segmentation
Object recognition
Undervisningsform : Alternating lectures (approx. 50% of scheduled time), laboratory exercises and course work assignments. Three compulsory course work assignments are to be worked out in groups/teams and documented in team reports.
Krævede forudsætninger : DSM3A or DSM4, or similar documented competences, i.e.
- Time and frequency domain analysis and filtering of sampled data. Time-frequency transforms (Fourier)
- Probabilistic analysis and modeling of sampled data, including prediction.
- Basic information theory: Entropy, coding and compression
- Matrix algebra and MATLAB
Anbefalede forudsætninger : -
Relationer : -
Prøveform : Se under bemærkninger
Censur : Intern
Bedømmelse : 7-trinsskala
Bemærkninger : Admission to the exam is pending on participation in the compulsory work assignments as well as on a satisfactory level of the team reports.

The exam has two phases:

- In the first phase each student makes a 10-minute presentation of a self-chosen topic from one of the work assignments, while the other group members are present. The actual assignment is to be decided on in advance.

- In the second phase each student makes a 10-minute presentation of a topic, drawn from the other two work assignments.

The grade given will be based on: the level of the team reports and the performance during the two presentations.
Undervisningsmateriale : Image and video processing. Thomas B Moeslund. ISBN 978-87-992732-0-1
Ansvarlig underviser : Volker Krüger , vok@cvmi.aau.dk