Image Processing and Analysis, 6 credits (TNM087)

Bildbehandling och bildanalys, 6 hp

Main field of study

Media Technology and Engineering

Level

First cycle

Course type

Programme course

Examiner

Reiner Lenz

Director of studies or equivalent

Camilla Forsell

Available for exchange students

Yes
Course offered for Semester Period Timetable module Language Campus VOF
6CMEN Media Technology and Engineering, M Sc in Engineering 5 (Autumn 2017) 2 2 Swedish/English Norrköping o

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 courseU, G1.5 credits
TEN1Written examinationU, 3, 4, 54.5 credits

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 HallSzeliski, (2010) Computer vision : algorithms and applications Springer

Additional literature

Books

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

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. 

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