Image Processing and Analysis, 6 credits

Bildbehandling och bildanalys, 6 hp

TNM087

Main field of study

Media Technology and Engineering

Course level

First cycle

Course type

Programme course

Examiner

Reiner Lenz

Director of studies or equivalent

Camilla Forsell

Education components

Preliminary scheduled hours: 40 h
Recommended self-study hours: 120 h

Available for exchange students

Yes
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Period Timetable module Language Campus ECV
6CMEN Media Technology and Engineering, M Sc in Engineering 5 (Autumn 2017) 2 2 Swedish/English Norrköping C

Main field of study

Media Technology and Engineering

Course level

First cycle

Advancement level

G2X

Course offered for

  • Media Technology and Engineering, M Sc in Engineering

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

Linear algebra, Calculus in several variables, Signals and systems, Matlab programming

Intended learning outcomes

The aim of the course is to give the students a theoretical and practical basis for computerized processing and analysis of digital images. After the course the student shall be able to:

  • describe the fundamental properties of the human visual system and the basic photometry concepts
  • describe the structure and properties of cameras
  • understand and use methods for generation of HDR images
  • construct and use simple linear and non-linear filters in the spatial domain
  • understand the connection between the spatial domain and the frequency domain
  • describe the principles of image filtering in the frequency domain
  • describe and implement simple methods for image segmentation
  • understand and use morphological operations on binary images
  • describe different methods for representation of objects in images
  • describe the principles of pattern recognition based on decision functions

Course content

The human visual system. Photometry. Image aquisition: camera properties, HDR images. Tone transformations. Filtering in the spatial domain. The Fourier transform, filtering in the frequency domain. Image restoration. Morphological operations. Segmentation. Representation of objects in images. Pattern recognition.

Teaching and working methods

The course is given in the form of lectures and laboratory work.

Examination

LAB1Laboratory course1.5 creditsU, G
TEN1Written examination4.5 creditsU, 3, 4, 5

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för teknik och naturvetenskap

Director of Studies or equivalent

Camilla Forsell

Examiner

Reiner Lenz

Course website and other links

http://www2.itn.liu.se/utbildning/kurs/

Education components

Preliminary scheduled hours: 40 h
Recommended self-study hours: 120 h

Course literature

Additional literature

Books

  • Gonzalez, Woods, (2008) Digital Image Processing Third edition Prentice Hall
  • Szeliski, (2010) Computer vision : algorithms and applications Springer
Code Name Scope Grading scale
LAB1 Laboratory course 1.5 credits U, G
TEN1 Written examination 4.5 credits U, 3, 4, 5

Regulations (apply to LiU in its entirety)

The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.

LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva. 

Additional literature

Books

Gonzalez, Woods, (2008) Digital Image Processing Third edition Prentice Hall
Szeliski, (2010) Computer vision : algorithms and applications Springer

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize
I U A Modules Comment
1. DISCIPLINARY KNOWLEDGE AND REASONING
1.1 Knowledge of underlying mathematics and science (G1X level)
X

                            
1.2 Fundamental engineering knowledge (G1X level)
X

                            
1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
X
X
LAB1
TEN1

                            
1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)

                            
1.5 Insight into current research and development work

                            
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
2.1 Analytical reasoning and problem solving
X
X
LAB1
TEN1

                            
2.2 Experimentation, investigation, and knowledge discovery

                            
2.3 System thinking

                            
2.4 Attitudes, thought, and learning
X

                            
2.5 Ethics, equity, and other responsibilities

                            
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
3.1 Teamwork

                            
3.2 Communications

                            
3.3 Communication in foreign languages

                            
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
4.1 External, societal, and environmental context

                            
4.2 Enterprise and business context

                            
4.3 Conceiving, system engineering and management

                            
4.4 Designing

                            
4.5 Implementing
X
X
LAB1
TEN1

                            
4.6 Operating

                            
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development

                            
5.2 Economic conditions for knowledge development

                            
5.3 Identification of needs, structuring and planning of research or development projects

                            
5.4 Execution of research or development projects

                            
5.5 Presentation and evaluation of research or development projects

                            

This tab contains public material from the course room in Lisam. The information published here is not legally binding, such material can be found under the other tabs on this page.

There are no files available for this course.