700.304 (18W) Fundamentals of Image Processing

to moodle

Wintersemester 2018/19

Registration deadline has expired.

First course session
03.10.2018 17:00 - 19:00 On Campus

... no further dates known

Overview

Lecturer

Dr. Saeed Yahyanejad, M.Sc.

Course title german

Fundamentals of Image Processing

Type

Lecture - Course (continuous assessment course )

Hours per Week

2.0

ECTS credits

4.0

Registrations

26 (50 max.)

Organisational unit

Institut für Intelligente Systemtechnologien

Language of instruction

English

Course begins on

03.10.2018

eLearning

Go to Moodle course

Time and place

List of events is loading...

Intended learning outcomes

This is an introductory course to the fundamentals of digital image processing. It provides the basic concepts to learn how to process an image in order to extract the desired information out of it.

By the end, students should:

be able to apply the basic methods of image processing,
have a good understanding of image features and object recognition,
be able to apply the acquired knowledge of image processing to solve related industrial and research problems.

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

Understanding the concept of image (e.g., camera technology, digital images, image types and representation, thermal images)
Simple image manipulations (e.g., color depth, size, cropping)
Lens distortion – Camera calibration
Image filtering and convolutions
Morphological transformation and thresholding
Geometric transformations
Feature 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).

Literature

Digital Image Processing (third Edition); Rafael C. Gonzalez, Richard E. Woods.
Computer Vision: Algorithms and Applications; Richard Szeliski.

Intended learning outcomes

This is an introductory course to the fundamentals of digital image processing. It provides the basic concepts to learn how to process an image in order to extract the desired information out of it.

By the end, students should:

be able to apply the basic methods of image processing,
have a good understanding of image features and object recognition,
be able to apply the acquired knowledge of image processing to solve related industrial and research problems.

Teaching methodology including the use of eLearning tools

Course content

Understanding the concept of image (e.g., camera technology, digital images, image types and representation, thermal images)
Simple image manipulations (e.g., color depth, size, cropping)
Lens distortion – Camera calibration
Image filtering and convolutions
Morphological transformation and thresholding
Geometric transformations
Feature 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).

Literature

Digital Image Processing (third Edition); Rafael C. Gonzalez, Richard E. Woods.
Computer Vision: Algorithms and Applications; Richard Szeliski.

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.

German
English

Examination methodology

Written Exam.

(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

Mainly conceptual questions with different difficulty range.

Few multiple choices may be included.

Examination methodology

Written Exam.

(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

Mainly conceptual questions with different difficulty range.

Few multiple choices may be included.

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)

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)
    - 700.304 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)

Masterstudium Mathematics (SKZ: 401, Version: 18W.1)
- Subject: Information and Communications Engineering (Compulsory elective)
  - 9.4 Fundamentals of Image Processing ( 2.0h VC / 4.0 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 2017/18

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)