460-4080 – Image Analysis I (ANO I)
| Gurantor department | Department of Computer Science |
| Subject guarantor | doc. Dr. Ing. Eduard Sojka |
| Study level | undergraduate or graduate |
Subject aims expressed by acquired skills and competences
The course provides the students with the foundations of image analysis. After passing the course, the student will understand the principles of the selected method of image segmentation and image analysis and will be able to implement them.
Teaching methods
Lectures
Tutorials
Summary
The following topics are discussed: Image segmentation, detecting edges, regions, and feature points. Measuring objects for recognition based on features. Classification using discriminant functions, classification based on clustering, classification using neural networks. Using deep neural networks for image analysis. Reconstructing 3D scenes. Analysing 3D point clouds. Processing images varying in time. Object tracking. Recognising actions from video frames. The course includes the computer labs in which the computer programs are realised corresponding to the mentioned topics.
Compulsory literature:
Mandatory:
Gonzalez, R., C., Woods, R., E.: Digital Image Processing, 4th Edition, Pearson, ISBN-13: 9780134734804, 9780133356724, 2018.
Aggarwal, CC: Neural Networks and Deep Learning, Springer, ISBN: 978-3-319-94463-0, 978-3-319-94462-3, 2018.
Recommended literature:
1. Burger, W., Burge, M., J.: Principles of Digital Image Processing: Fundamental Techniques, Springer, ISBN-10: 1848001908, ISBN-13: 978-1848001909, 2011
2. Brahmbhatt, S.: Practical OpenCV (Technology in Action), Apress, ISBN-10: 1430260793, ISBN-13: 978-1430260790, 2013
3. Petrou, M., Petrou, C.: Image Processing: The Fundamentals, Wiley, ISBN-10: 047074586X, ISBN-13: 978-0470745861, 2010
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.