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Slides

This material is copyrighted (c) 2014-2016 by Dr.-Ing. Stefan Steidl, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany. It is based on the former lectures Mustererkennung I & II by Prof. Dr.-Ing. Heinrich Niemann and the replacing lectures by Prof. Dr.-Ing. Joachim Hornegger and Elli Angelopoulou, PhD. Use without prior written permission of the authors is not permitted!

 

 

News:

The lecture on Friday 18th of January is cancelled!

The lecture on Tuesday 22th of January will be a summary of the lecture where you can ask questions.

Please register in the secretary for the exams (Tuesday-Thursday 8am - 4pm and Monday and Friday 8am - 12am). Some of them are english speaking only!

In the week before christmas, the secretary is open Mo-Th 8am-12am!

 

Dates:

Wednesday 20.02.2019

Thursday 21.02.2019

Friday 22.02.2019

Thursday 14.03.2019

Friday 15.03.2019

Wednesday 10.04.2019

Thursday 11.04.2019

Friday 12.04.2019

These slides are part of a presentation. The presentation is not complete without the verbal explanations given during the lecture.

The pdf files are password protected. You will get the password during the first lecture.

Three different versions of the slides are available:

  1. The 'screen' version are the slides presented during the lectures. They may contain embedded video and audio files leading to large file sizes. Furthermore, they use extensively overlays, i.e. slides are displayed incrementally, resulting in a sequence of pdf pages instead of a single one just showing the final outcome. Hence, this version is not suited for printing. The slides are best viewed with a software that is able to show overlays without transition effects (e.g. GoodReader for iPad).
  2. 'Print (A5)' shows two slides per page and is intended for printing booklets in the DIN A5 format. Let the printer driver rearrange the pages and use duplex printing. The printed versions do not contain video and audio files and most important, they do not have overlays. The printed versions include some slides that are especially designed for printing: for example, in a presentation, the difference between two similar images can be best viewed if both images are overlaid. As this is not possible in a print-out, both images are printed next to each other instead.
  3. 'Print (A6)' shows four slides per page. Besides the different arrangement of slides per page, the slides are identical to the other print version. This is the standard option for printing if you want to file your print-outs in a folder.

We will update the slides during the semester as needed in order to improve the quality of our slides.
Please make sure that you have the latest version of our slides in preparation for the exam!

 

 

Chapter Lecture

Slides

Date (Week) SlidesScreen
Print (A5)Print (A6) Update
1 Introduction 16.10.2018 (1) 1-1 1-55 Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
2 Key concepts of pattern recognition19.10.2018 (1) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
3 Analog to digital conversion: sampling23.10.2018 (2) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
4 Analog to digital conversion: quantization26.10.2018 (2) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
5 Histogram equalization02.11.2018 (3) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
6 Thresholding and binarization02.11.2018 (3) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
7 Filtering: noise suppression06.11.2018 (4) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
8 Edge detection16.11.2018 (5) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
9 Non-linear filtering19.11.2018 (6) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
10Normalization23.11.2018 (6) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
11Feature extraction: heuristic methods23.11.2018 (6)

1-65

Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf23.11.2018
27.11.2018 (7)66-131
12Feature extraction: analytic methods Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
13Numerical optimization11.12.2018 (9) Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
14Feature selection Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
15Statistical classification Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
16Polynomial classifier08.01.2019 Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
17Non-parametric classifiers08.01.2019 Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf
18Kalman filter11.01.2019 Initiates file downloadpdfInitiates file downloadpdfInitiates file downloadpdf11.01.2019 3pm

 

Additional material

Python code examples are shown during the lecture.
The algorithms are demonstrated using IPython Notebook.

Getting familiar with the algorithms is essential and will be part of the oral exams. This is true for both the 5.0 ECTS and the 7.5 ECTS exams. Please make sure that you have the latest version of the files as they might be updated.