Image Processing

Contents: In this course, we teach the fundamentals of image processing, starting from the human visual system and the basics of digital image acquisition. The goal is to understand the technical and theoretical basis of image processing and to be able to implement basic algorithms in practice.

 

Time and Location

  • Monday, 10:15 to 11:45, Room: B 6, A203, Start: 4.9..2017
  • Monday, 12:00 to 13:30, Room: B 6, A203

Instructor

Final mark

  • exam

Slides and Excercises

  1. Slideset:

Participation 

  • The course is open to students of the Master Business Informatics, Master Business Mathematics and Mannheim Master in Data Science (MMDS). 
  • The course is restricted to 30 participants.
  • Places are assigned on first come/first serve basis.
  • Students register for the course by email to me.

Requirements

  • Basic programming skills in C++ are beneficial for the exercise.
  • Basics in linear algebra are beneficial for the lecture

Outline

Week

Topic

04.09.2017

General Remarks

Human Visual System

11.09.2017

Basics of Imaging

18.09.2017

Noise and Basic Image Operations

25.09.2017

Energy Minimization

02.10.2017

Variational Methods

09.10.2017

Image Segmentation

16.10.2017 Image Segmentation
23.10.2017 Feature Extraction
30.10.2017 Classification

06.11.2017

Classification

13.11.2017

Image Sequences, Optical Flow

20.11.2017

Point Matching

27.11.2017

Stereo Vision

04.12.2017  

 Literature 

  • R. Szeliski: Computer Vision Algorithms and Applications, Springer, 2010. ISBN: 978-1-84882-934-3. (Online available: http://szeliski.org/Book/)

Software

  • C++
  • Python