700.304 (17W) Fundamentals of Image Processing

Wintersemester 2017/18

Registration deadline has expired.

First course session
22.01.2018 09:00 - 18:00 B01.0.203 On Campus
... no further dates known

Overview

Lecturer
Course title german Fundamentals of Image Processing
Type Lecture - Course (continuous assessment course )
Hours per Week 2.0
ECTS credits 4.0
Registrations 11 (50 max.)
Organisational unit
Language of instruction English
possible language(s) of the assessment German
Course begins on 22.01.2018
eLearning Go to Moodle course

Time and place

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Course Information

Intended learning outcomes

The students

  • are able use the basic methods for image processing,
  • have a good command of the machine learning approaches for the description of image features and object recognition,
  • are able to transfer the acquired knowledge of image processing to solve complex applications for industry and research,
  • are able to describe the state-of-the-art of the presented topics

Teaching methodology including the use of eLearning tools

The course has two major parts. The first part consists of the theoretical and methodic fundamentals that will be introduced during the lecture. The second part consists of intensive lab work where students can implement, test, and apply the presented methods. The major lab language will be Matlab but additional programming languages will be introduced like C++ (OpenCV) and Python.

Course content

  • Introduction (color systems & image formats                    
  • Image Transformations                                                    
  • Image Filtering                                                        
  • Morphology                                                      
  • Edge Detection                                                            
  • Polygon and Corner Detection                                                            
  • Image Interpolation                                                           
  • Invariant Features   
  • Camera Calibration                                                         
  • Scale invariant feature transform                                                       
  • Object Recognition
  • Autonomous Vehicles 

Prior knowledge expected

Basic knowledge of any programming language

Literature

Machine Vision, E.R. DaviesElsevier, Third EditionISBN-10: 0122060938ISBN-13: 978-0122060939Digital Image Processing (3rd Edition)[Hardcover] Rafael C. Gonzalez (Author), Richard E. Woods (Author)ISBN-10: 013168728XISBN-13: 978-0131687288

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

Written Exam + Project 

Examination topic(s)

The student should pass a written exam successfully which reflects the understanding of the presented concepts and approaches. Additionally, the students should design and implement a fully working system in the field of machine learning.

Assessment criteria / Standards of assessment for examinations

The final evaluation is divided as follows:

70% Exam

30%  Project

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 VC / 3.0 ECTS)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 4.0 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 VO / 3.0 ECTS)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 4.0 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)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 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)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 4.0 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)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 4.0 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)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 4.0 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)
        • 700.304 Fundamentals of Image Processing (2.0h VC / 4.0 ECTS)

Equivalent courses for counting the examination attempts

Wintersemester 2023/24
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2022/23
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2021/22
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2020/21
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2019/20
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2018/19
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2016/17
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2015/16
  • 700.304 VC Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2014/15
  • 700.304 VK Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2013/14
  • 700.304 VK Fundamentals of Image Processing (2.0h / 4.0ECTS)
Wintersemester 2012/13
  • 700.304 VK Fundamentals of Image Processing (2.0h / 4.0ECTS)