Computer-Assisted Image Analysis I

5 credits

Course, Master's level, 1TD396

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 November 2026–17 January 2027
Language of instruction
English
Entry requirements

120 credits including 30 credits in mathematics and 10 credits in computer science, including Scientific Computing I/Introduction to Scientific Computing and Computer Programming I, Proficiency in English equivalent to the Swedish upper secondary course English 6.

Application deadline
15 April 2026
Application code
UU-12030

Admitted or on the waiting list?

Registration period
19 October 2026–8 November 2026
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 November 2026–17 January 2027
Language of instruction
English
Entry requirements

120 credits including 30 credits in mathematics and 10 credits in computer science, including Scientific Computing I/Introduction to Scientific Computing and Computer Programming I, Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
19 October 2026–8 November 2026
Information on registration from the department

About the course

Have you worked with photos, using photo digital software? You might have improved the focus of a blurry photo. If that is the case, you have worked with digital image analysis. In digital image analysis, we deal with the problem of automatically transforming images into information and, at its best, into knowledge. There are many applications, e.g. in forestry and agriculture, environmental supervision, astronomy, medicine and industrial quality control. The image can come from a microscope, a computer tomograph, a TV camera, a satellite or a telescope. The size of the image can range from a few micrometres to light-years. The aim can be analysis made by the human eye or a computerised analysis.

Through the use of computers and mathematical transformations, the image can be improved to make a visual interpretation easier. Data such as size, texture and number can be found in the image. The data can be processed statistically leading to an interpretation and a decision.

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