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The exercise courses take place on:

Tuesdays 10:15 - 11:00 (02.133-113)

Tuesdays 16:15 - 17:00 (02.134-113)

Both courses cover the same topics.

If there are any questions or problems regarding the exercises that could not be clarified within the courses, feel free to come by or write to Opens window for sending emailDaniel Stromer.


  • 01.11.2016

    The exercise session on Nov 1 is cancelled due to a public holiday!

Welcome to the Exercises for Introduction to Pattern Recognition!

The topics are practical tasks that are relatively closely related to the lecture. Please keep in mind that this is the first year where the exercise will be part of the exam.

Both exercise sessions cover the same content. For all exercises, Opens external link in new windowJupiter Notebooks will be provided where you have to fill in code snippets.


A single session will typically take about 45-60 minutes. Exercise sheets and their solutions will become available on this website.

Older lecture videos are available at Opens external link in new window (only accessible if you are inside the university network; if you want to watch the videos from home, consider to tunnel the connection). Be aware that the contents of the lecture have changed since then!


Some remarks about programming

We will shortly go over the Python code for the practical exercises in the sessions. The solutions will be provided (password-protected) after another week. The password will be announced in the next sessions, or by request (write me an Opens window for sending emailemail).



Exercise Date
1 Introduction to Python   18.10.2016
2 Plotting and Imaging25.10.2016
3 Sampling and k-Means Clustering (updated on 07.11.16)08.11.2016
4 Histogram Equalization, Image Tresholding and Filtering15.11.2016
5 Image Sharpening and Edge Detection22.11.2016
6 Simple Segmentation and Morphological Operations29.11.2016
7 Morphological Operations and Recursive Filters06.12.2016
8 Normalization13.12.2016
9 Discrete Fourier Transform20.12.2016

2-D Filtering in Fourier Domain 

Walsh-Hadamard Transform

11 Wavelet transforms for image compression17.01.2017
12 Eigenfaces24.01.2017
13 Classification31.01.2017
14 Refresher07.02.2017