CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

# Image Processing and Analysis

Code Completion Credits Range Language
17PMP2ZAO Z,ZK 4 2P+2C Czech
Lecturer:
Zoltán Szabó (guarantor), Václav Hlaváč
Tutor:
Zoltán Szabó (guarantor), Václav Hlaváč, Marek Piorecký
Supervisor:
Department of Biomedical Informatics
Synopsis:

The subject teaches students how to process images by a computer. First, the digital processing methods will be explained, when there is not information about image semantics. Second, the image analysis methods will be explained, in which the knowledge about the image content is available. This allows to segment object in images, describe them by features and recognize them.

Requirements:

It is possible to obtain 100 points in total. Fulfillment of the exercises during the practices corresponds to maximum 60 points and the written exam test from the lectures assures maximum 40 points. Classification &lt;50 F, 50-59 E, 60-69 D, 70-79 C, 80-89 B, 90-100 A

Syllabus of lectures:

1.Digital image processing × image analysis × computer vision. Interpretation, its significance for images. Objects in images.

2.Distance transform (DT). Brightness histogram. Image acquisition from the geometric and radiometric point of view.

3.Fourier transform. Sampling theorem.

4.Filtering in frequency domain.

5.PCA.

6.Brightness scale transformation.

7.Geometric transformations, interpolation.

8.Image registration.

9.Image processing in spatial domain. Convolution, correlation.

10.Noise filtering. Edge detection. Linear and nonlinear methods.

11.Mathematical morphology.

12.Image compression. Color images. Texture.

13.Segmentation of objects in images.

14.Objects description in images and their recognition.

Syllabus of tutorials:

1.Grayscale mathematical morphology, dilation, erosion

2.Top Hat transform, distance transform.

3.Fourier transform.

4.Filtering in frequency domain.

5.Principal Component Analysis (PCA).

6.Brightness scale transformation.

7.Geometric transformations, interpolation.

8.Image registration.

9.Image processing in spatial domain. Convolution, correlation.

10.Noise filtering. Edge detection. Linear and nonlinear methods.

11.Image compression. Color images.

12.Huffman coding, Discrete cosine transform (DCT).

13.Segmentation of objects in images.

14.Summary of subject topics.

Study Objective:

The goal of the subject is to introduce the basic principles of image processing and analysis. We link to the student knowledge from the signal theory.

Study materials:

[1] Šonka M., Hlaváč V., Boyle R.: Image, processing, analysis and machine vision, Cengage Learning;, Canada, 4th edition, 2014, 912 pages, ISBN-13: 978-1133593607.

Note:
Time-table for winter semester 2019/2020:
 06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00 roomKL:B-435Piorecký M.10:00–11:50(lecture parallel1parallel nr.1)Kladno FBMIPočítačová učebna roomKL:B-420Szabó Z.Hlaváč V.10:00–11:50(lecture parallel1)Kladno FBMIUčebna
Time-table for summer semester 2019/2020:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2020-04-01
For updated information see http://bilakniha.cvut.cz/en/predmet4719606.html