Image Processing

2018/2019

Prerequisite/Recommended prerequisite for participation in the module

Mathematics for Multimedia Applications

Content, progress and pedagogy of the module

Cameras capture visual data from the surrounding world. Building systems which can automatically process such data requires image processing methods. Students who complete the module will understand the nature of digital images and have an overview of different theories and methods within image processing and their applicability.

Learning objectives

Knowledge

Students who complete the course module will obtain the following qualifications:

  • Must have knowledge about the primary parameters of the camera and lens
  • Must have knowledge about the representation of a digital image
  • Must be able to understand the general framework of image processing
  • Must be able to understand and interpret image histograms
  • Must be able to understand color images and their different representations
  • Must be able to understand the principle of point processing
  • Must be able to understand principle of neighborhood processing
  • Must be able to understand what a BLOB is and how it can be extracted
  • Must be able to understand how moving objects can be segmented in a video sequence

Skills

Students who complete the course module will obtain the following qualifications:

  • Must be able to apply the following point processing methods: grey-level mapping, histogram stretching, thresholding and image arithmetic
  • Must be able to apply the following neighborhood processing methods: median filter, mean filter and edge detection
  • Must be able to apply the following morphologic operations: dilation, erosion, opening and closing
  • Must be able to apply basic feature extraction and matching
  • Must be able to apply image differencing and background subtraction
  • Must be able to apply geometric transformations to an image

Competences

Students who complete the course module will obtain the following qualifications:

  • Must be able to apply the general framework of image processing in a new context. This includes  choosing the relevant methods and evaluating the output
  • Must be able to combine different morphologic operations and understand the resulting effect they have on a binary image

Type of instruction

Refer to the overview of instruction types listed in the start of chapter 3. The types of instruction for this course are decided in accordance with the current Framework Provisions and directions are decided and given by the Study Board for Media Technology.

Exam

Exams

Name of examImage Processing
Type of exam
Written or oral exam
In accordance with the current Framework Provisions and directions on examination from the Study Board for Media Technology:
Individual oral or written examination with internal censor. The assessment is performed with the Pass/Fail grade.
ECTS5
Permitted aids
With certain aids:
See Semester Description
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentThe criteria for the evaluation are specified in the Framework Provisions.

Facts about the module

Danish titleBilledbehandling
Module codeMSNMEDB3103
Module typeCourse
Duration1 semester
SemesterAutumn
ECTS5
Language of instructionEnglish
Location of the lectureCampus Aalborg, Campus Copenhagen
Responsible for the module

Organisation

Study BoardStudy Board of Media Technology
DepartmentDepartment of Architecture, Design and Media Technology
FacultyTechnical Faculty of IT and Design