700.302 (18W) Labor "Fundamentals of Image Processing"

Wintersemester 2018/19

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First course session
03.10.2018 15:00 - 17:00 L4.1.02 ICT-Lab Off Campus
... no further dates known

Overview

Lecturer
Course title german Labor "Fundamentals of Image Processing"
Type Course (continuous assessment course )
Hours per Week 2.0
ECTS credits 3.0
Registrations 13 (25 max.)
Organisational unit
Language of instruction English
Course begins on 03.10.2018
eLearning Go to Moodle course

Time and place

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Course Information

Intended learning outcomes

This is an introductory Lab. course to the fundamentals of digital image processing using MATLAB. It introduces the image processing functions and algorithms in MATLAB which enables you to apply your knowledge of image processing in real scenarios.

By the end,  students should be able to program the presented methods of image processing in MATLAB and also extend the concepts to the new applications and programming languages.

Teaching methodology including the use of eLearning tools

The fundamentals will be presented according to well-known literature and references. An extension to the basics and further details will be presented interactively according to the potentials of the students.

Course content

  • Accessing the images and data-types in MATLAB
  • Simple image manipulations (e.g., color depth, size, cropping)
  • Image filtering and convolutions
  • Morphological transformation and thresholding
  • Geometric transformations
  • Feature / Color detection
  • Image registration and stitching
  • Image restoration (e.g., de-blurring, interpolations, Fourier domain)

Prior knowledge expected

Basic knowledge of Mathematics (matrices and their operations).

Basic knowledge of programming.

Literature

  • Digital Image Processing using MATLAB (Second Edition); Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins,.

Intended learning outcomes

This is an introductory Lab. course to the fundamentals of digital image processing using MATLAB. It introduces the image processing functions and algorithms in MATLAB which enables you to apply your knowledge of image processing in real scenarios.

By the end,  students should be able to program the presented methods of image processing in MATLAB and also extend the concepts to the new applications and programming languages.

Teaching methodology including the use of eLearning tools

The fundamentals will be presented according to well-known literature and references. An extension to the basics and further details will be presented interactively according to the potentials of the students.

Course content

  • Accessing the images and data-types in MATLAB
  • Simple image manipulations (e.g., color depth, size, cropping)
  • Image filtering and convolutions
  • Morphological transformation and thresholding
  • Geometric transformations
  • Feature / Color detection
  • Image registration and stitching
  • Image restoration (e.g., de-blurring, interpolations, Fourier domain)

Prior knowledge expected

Basic knowledge of Mathematics (matrices and their operations).

Basic knowledge of programming.

Literature

Digital Image Processing using MATLAB (Second Edition); Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins,.

Examination information

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Examination methodology

Project assignment: You will receive couple of assignments , which you need to use the image processing functions and algorithms that you learned to solve them. You may be asked also to give an oral explanation regarding your codes.

(Class activities and answering questions will be extra points and will help if you do not perform well at the final exam).

Examination topic(s)

From the topics covered by the lectures during the course.

Assessment criteria / Standards of assessment for examinations

Project assignment and oral explanation.

Examination methodology

Project assignment: You will receive couple of assignments , which you need to use the image processing functions and algorithms that you learned to solve them. You may be asked also to give an oral explanation regarding your codes.

(Class activities and answering questions will be extra points and will help if you do not perform well at the final exam).

Examination topic(s)

From the topics covered by the lectures during the course.

Assessment criteria / Standards of assessment for examinations

Project assignment and oral explanation.

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
    • Subject: Information Technology (Compulsory elective)
      • 2.6 Bildverarbeitung ( 2.0h KS / 3.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
          Absolvierung im 5. Semester empfohlen
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Information Technology (Compulsory elective)
      • Bildverarbeitung ( 2.0h KU / 3.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Subject: Informationstechnische Vertiefung (Compulsory elective)
      • 10a.3 Wahl von Lehrveranstaltungen ( 0.0h VO/VC/KS/UE / 6.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
  • Bachelor's degree programme Information Technology (SKZ: 289, Version: 12W.2)
    • Subject: Informationstechnische Vertiefung (Compulsory elective)
      • Wahl von Lehrveranstaltungen ( 0.0h VK/VO/KU / 6.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Information and Communications Engineering: Supplements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Technical Complements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Information and Communications Engineering: Supplements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Technical Complements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.302 Labor "Fundamentals of Image Processing" (2.0h KS / 3.0 ECTS)

Equivalent courses for counting the examination attempts

Wintersemester 2023/24
  • 700.302 KS Lab: Fundamentals of Image Processing (2.0h / 3.0ECTS)
Wintersemester 2022/23
  • 700.302 KS Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2021/22
  • 700.302 KS Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2020/21
  • 700.302 KS Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2019/20
  • 700.302 KS Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2015/16
  • 700.302 KS Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2014/15
  • 700.302 KU Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2013/14
  • 700.302 KU Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)
Wintersemester 2012/13
  • 700.302 KU Labor "Fundamentals of Image Processing" (2.0h / 3.0ECTS)