DD2423 Image Analysis and Computer Vision 7.5 credits

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Please note

The information on this page is based on a course syllabus that is not yet valid.

A course in computer science focusing on basic theory, models, and methods for computer vision, image analysis and image processing.

  • Education cycle

    Second cycle
  • Main field of study

    Computer Science and Engineering
  • Grading scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 19 bildat19 for programme students

Autumn 19 for Study Abroad Programme (SAP)

  • Periods

    Autumn 19 P2 (7.5 credits)

  • Application code

    10095

  • Start date

    28/10/2019

  • End date

    14/01/2020

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places

    No limitation

  • Course responsible

    Mårten Björkman <celle@kth.se>

  • Teacher

    Tony Lindeberg <tony@kth.se>

  • Application

    Apply for this course at antagning.se through this application link.
    Please note that you need to log in at antagning.se to finalize your application.

Autumn 18 bildat18 for programme students

Autumn 18 SAP for Study Abroad Programme (SAP)

  • Periods

    Autumn 18 P2 (7.5 credits)

  • Application code

    10086

  • Start date

    29/10/2018

  • End date

    14/01/2019

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places

    No limitation

  • Course responsible

    Mårten Björkman <celle@kth.se>

  • Teacher

    Tony Lindeberg <tony@kth.se>

  • Target group

    Only open for students within the SAP-programme.

Autumn 18 Doktorand for single courses students

  • Periods

    Autumn 18 P2 (7.5 credits)

  • Application code

    10202

  • Start date

    29/10/2018

  • End date

    14/01/2019

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places *

    Max. 1

    *) If there are more applicants than number of places selection will be made.

  • Course responsible

    Mårten Björkman <celle@kth.se>

  • Teacher

    Mårten Björkman <celle@kth.se>

    Tony Lindeberg <tony@kth.se>

  • Target group

    For doctoral students at KTH.

Intended learning outcomes

After completing the course with a passing grade the student should be able to:
• identify basic concepts, terminology, models and methods in computer vision and image processing
• develop and evaluate a number of basic methods in computer vision and image processing systematically
• choose and apply methods for processing of image data related to image filtrering, image enhancement, segmentation, classification and representation,
• account for basic methods in computer vision as multiscale representation, detection of edges and other distinctive features, stereo, movement and object recognition to
• later as a working professional be able to decide how basic possibilities and limitations influence the choice of methods in image processing and computer vision for specific applications
• independently be able to implement, analyse and evaluate simple methods for computer vision and image processing
• be able to read and apply professional literature in the area.

Course main content

Overview about aims and methods for image analysis, image processing and computer vision. Orientation about biological seeing and visual perception. Properties of the perspective image formation.

Basic image analysis: signal theoretical methods, filtering, image enhancement, image reconstruction, segmentation, classification, representation.

Basic computer vision: multiscale representation, detection of edges and other distinctive features. Stereo and multi-camera systems. Object recognition, morphology.

Disposition

Eligibility

Recommended prerequisites

The courses in the basic block on mathematics, computer science and numerical analysis on the D-, E- or F-programme. One more course on signal processing and/or numerical analysis can be recommended. We recommend the students to read the course during the fourth year because it uses prerequisites from a relative wide spectrum of applied mathematics and computer science.

Literature

The reading list is announced on the course page.

Required equipment

Examination

  • LAB1 - Laboratory Work, 4.0, grading scale: A, B, C, D, E, FX, F
  • TEN1 - Examination, 3.5, grading scale: A, B, C, D, E, FX, F

In agreement with KTH´s coordinator for disabilities, it is the examiner who decides to adapt an examination for students in possess of a valid medical certificate. The examiner may permit other examination forms at the re-examination of few students.

Requirements for final grade

Offered by

EECS/Intelligent Systems

Contact

Mårten Björkman, e-post: celle@kth.se

Examiner

Mårten Björkman <celle@kth.se>

Supplementary information

The course has replaced DD2422 Image Analysis and Computer Vision.

Version

Course syllabus valid from: Autumn 2019.
Examination information valid from: Spring 2019.