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The course teaches how to represent, process and interpret 2D image in a computer. The first part of the course will be focused on image processing taken similarly as in signal processing, i.e. without interpretation. We will explain image acquisition, linear and non-linear pre-processing and image compression. In the second part, we will teach students the segmentation and registration methods for 2D images. The gained knowledges will be applied to practical examples in exercises, so that students will gain a practical experience with the topic.
It is assumed that students of this course have a working knowledge of mathematical analysis, linear algebra, probability theory and statistics. In addition, basic programming skills, mainly in MATLAB, are expected. This master subject should not repeat the knowledge, which was taught in the Open informatics study program in bachelor studies. The subject would be too shallow otherwise.
It could happen that some students did not study the topics, which are considered a prerequisite of the subject Autonomous robotics. They have to study or refresh their knowledge on their own. Some other knowledge/skills might be useful in the subject labs.
I offer students the aid to refresh their knowledge by providing them presentations related to the topic.
Lecturer: Václav Hlaváč, Radoslav Škoviera (exceptionally, when Václav Hlaváč travels or is sick).
Work load: 2 h lecture + 2 h exercises/labs + 5 h home work per week.
Slides for lectures are available in English on http://people.ciirc.cvut.cz/~hlavac/TeachPresEn/ and in Czech on http://people.ciirc.cvut.cz/~hlavac/TeachPresCz/. I usually improve the slides, when I am preparing for a particular lecture.
Instructors: Radoslav Škoviera (vedoucí cvičení), Dominik Fiala, Júlia Škovierová.
Details about laboratory and seminars could be found in section labs.