Image Analysis

Course guarantor:

Václav Hlaváč

Lecturer:

Václav Hlaváč, Zoltán Szabó

Tutor:

Radim Krupička, Zoltán Szabó

Supervisor:

Department of Biomedical Informatics

Synopsis:

The course aims to acquaint students with methods of image processing and analysis. The course is taught in English. The course will teach students how to process and analyze images on a computer. We will explain digital image processing methods where we do not have semantic knowledge about the image's content. We will also study image analysis procedures, where we can segment objects from the background according to semantics, describe them with features and recognize them. We will build on the student's knowledge of mathematical analysis, linear algebra, and signal theory.

Requirements:

Credit conditions:

Participate in the exercise (2 absences recognized by prior apology are allowed).

Get at least 50% of the points from the exercise. Points can be obtained from the test, homework, and, last but not least, by submitting exercises.

Test conditions:

Only students entitled to a credit from the exercises can be tested.

The exam has two parts, written and oral.

The final grade is determined by the sum of points from the exercises (max. 40 points), the written part (max. 30 points), and the oral part (max. 30 points).

The total number of achievable points is therefore 100. A 100-90 points, B 89-80 points, C 79-70 points, D 69-60 points, E 59-50 points, F <50 points.

Syllabus of lectures:

1.Image Processing vs. computer vision. Role of interpretation. Objects in the image. Digital image.

2.Distance transformation. Obtaining images from a geometric and radiometric point of view.

3.Fourier Transform. Sampling.

4.Frequency filtering of the image. Principal Component Analysis (PCA).

5.Transformation of brightness, geometric transformation, interpolation.

6.Image processing in the spatial domain. Convolution, correlation.

7.Noise filtering. Edge detection.

8.Mathematical morphology.

9.Object segmentation in images.

10.Segmentation using chart optimization.

11.Object description in images.

12.Object recognition in images.

13.Image registration and registration of objects in images.

14.Color images. Image compression.

Syllabus of tutorials:

1.Image Processing vs. computer vision. Role of interpretation. Objects in the image. Digital image.

2.Distance transformation. Obtaining images from a geometric and radiometric point of view.

3.Fourier Transform. Sampling.

4.Frequency filtering of the image. Principal Component Analysis (PCA).

5.Transformation of brightness, geometric transformation, interpolation.

6.Image processing in the spatial domain. Convolution, correlation.

7.Noise filtering. Edge detection.

8.Mathematical morphology.

9.Object segmentation in images.

10.Segmentation using chart optimization.

11.Object description in images.

12.Object recognition in images.

13.Image registration and registration of objects in images.

14.Color images. Image compression.

Study Objective:

Study materials:

Note:

Further information:

http://people.ciirc.cvut.cz/~hlavac/teaching/FBMI-ZAO/2023-2024Zima/

Time-table for winter semester 2025/2026:

	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
Mon
Tue
Wed
Thu	roomKL:B-520 Krupička R. Szabó Z. 08:00–09:50 (lecture parallel1 parallel nr.1) Kladno FBMI roomKL:B-420 Hlaváč V. Szabó Z. 10:00–11:50 (lecture parallel1) Kladno FBMI
Fri

Time-table for summer semester 2025/2026:

Time-table is not available yet

The course is a part of the following study plans:

• Software Technologies (compulsory course)