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FEKT-MPA-AB2Acad. year: 2023/2024
The subject is designed as an extension of the previous subject Image processing and analysis, which is taught in the 3rd semester of the master's study program. The form of teaching is project-based, where students solve assigned tasks from various areas of image data processing within selected teams. Specifically, these areas are: image noise suppression, image restoration, landmark detection and feature extraction, stereoscopy, camera calibration methods, disparity map estimation, 3D object reconstruction, advanced methods for image matching, object tracking, and optical-based motion detection flow, image segmentation.
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Number of ECTS credits
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Offered to foreign students
Entry knowledge
1) Processing and analysis of signals (theory of analogue and digital signals, filtering, Fourier and wavelet transformation, spectral analysis).
2) Processing and analysis of images and other multidimensional signals (theory of nD signals, image restoration methods, image segmentation methods, texture analysis, image data reconstruction methods).
3) Basic knowledge of machine learning methods and statistical analysis (linear classifiers, clustering methods, neural networks, SVM, PCA, probability theory).
4) Mathematics at the technical college level (derivatives, integrals, solving integrodifferential equations, optimization tasks).
5) Advanced programming experience (MATLAB or Python)
The main prerequisite is the successful completion of the previous course MPA-ABO (Analysis of Biomedical Images). The composition of the MPA-AB2 course is closely related to the material discussed in this course (MPA-ABO).
Rules for evaluation and completion of the course
The conditions for successful completion of the course are determined by the annually updated Announcement of the subject guarantee.
- full participation in lectures and exercises
- preparation and delivery of a presentation on a given topic
- success in the final exam (the condition for passing the course is to obtain at least 50 points in total)
Aims
The course aims to familiarize students in the last semester of the master's study program with selected advanced methods in the field of image processing and computer vision, which are applicable to a wide range of applications. The goal is to acquire the appropriate theoretical basis of the discussed methods and, within team projects, to be able to practically apply the acquired knowledge in order to solve the selected task.
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Elearning
Classification of course in study plans
Exercise in computer lab
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Syllabus