460-4080/02 – Image Analysis I (AO1)

Gurantor departmentDepartment of Computer ScienceCredits4
Subject guarantordoc. Dr. Ing. Eduard SojkaSubject version guarantordoc. Dr. Ing. Eduard Sojka
Study levelundergraduate or graduate
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
GAU01 Ing. Jan Gaura, Ph.D.
SOJ10 doc. Dr. Ing. Eduard Sojka
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 10+0

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. Graduates of this course will be able to: - Describe selected methods of image segmentation, image analysis, video analysis, and 3D model reconstruction from images. - Describe methods for detecting and classifying objects in images using various types of neural networks. - Design, invent, develop, implement, and test algorithms in the above-mentioned areas. - Assess, evaluate, compare, and recommend algorithms and software products that solve problems in the above-mentioned areas.

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. Graduates of this course will be able to: - Describe selected methods of image segmentation, image analysis, video analysis, and 3D model reconstruction from images. - Describe methods for detecting and classifying objects in images using various types of neural networks. - Design, invent, develop, implement, and test algorithms in the above-mentioned areas. - Assess, evaluate, compare, and recommend algorithms and software products that solve problems in the above-mentioned areas.

Compulsory literature:

1. Sojka, E., Gaura, J., Krumnikl, M.: Matematické základy digitálního zpracování obrazu, VŠB-TU Ostrava, 2011. 2. Sojka, E.: Digitální zpracování a analýza obrazů, učební texty, VŠB-TU Ostrava, 2000 (ISBN 80-7078-746-5). 3. Gonzalez, R., C., Woods, R., E.: Digital Image Processing, 4th Edition, Pearson, ISBN-13: 9780134734804, 9780133356724, 2018. 4. Simon J.D. Prince: Understanding Deep Learning, 2023, https://anthology-of-data.science/resources/prince2023udl.pdf 5. Szeliski, R.: Computer Vision: Algorithms and Applications, Springer, ISBN 9783030343712, 9783030343729 (eBook), 2022. 6. Gonzalez, R., C., Woods, R., E.: Digital Image Processing, 4th Edition, Pearson, ISBN-13: 9780134734804, 9780133356724, 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

Additional study materials

Way of continuous check of knowledge in the course of semester

Conditions for granting the credit: The tasks that are included into the program of exercises must be worked out and submitted to the teacher for evaluation. Oral exam.

E-learning

https://lms.vsb.cz

Other requirements

No further requirements are imposed.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: - Detecting edges in images, gradient methods, zero-crossing method, parametric edge models. - Image segmentation by region growing/splitting, thresholding, optimal threshold selection, adaptive thresholding. - Canny edge detector, Hough transform. - Detecting the feature points in images. - Measuring the objects for recognition, selecting and computing the descriptors. - Evaluating the efficiency of descriptors, introduction to universal descriptors (HoG). - Classification using discriminant functions, clustering, and SVM. - Classification using classical shallow neural networks. - Introduction to the deep neural networks, network architectures for detecting and recognising objects in images. - Introduction to generative networks (GAN networks, diffusion networks). - Creating 3D models from images, camera calibration, 3D sensors, lidars. SLAM - The problem of finding the correspondence between the images, and some methods for its solution. - Analysis of 3D point clouds, detecting the feature points, computing the descriptors, geometric consistency, recognising objects in point clouds. - Analysis of images changing in time, optical flow, object tracking, Kalman filtering. Recurrent neural networks LSTM, self-attention networks). - Introduction to action recognition from video sequences. Computer labs: - Edge detection, gradient and zero-crossing methods. - Canny edge detector, parametric edge models. - Thresholding, optimal threshold selection. - Hough transform. - Selecting the features/descriptors for classification. - Optimizing the set of descriptors, universal descriptors (HoG). - Classification using etalons and discriminant functions. - Classification using k-means clustering, classification using SVM. - Classification using shallow neural networks. - Classification using deep neural networks. - Examples of generative network usage. - Optical flow. - Tracking the objects in video frames. - Obtaining the credit.

Conditions for subject completion

Full-time form (validity from: 2021/2022 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)		Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 40  21
        Examination Examination 60  30 3
Mandatory attendence participation: 80%

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

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Part-time form (validity from: 2021/2022 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)		Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 40  21
        Examination Examination 60  30 3
Mandatory attendence participation: 80%

Show history

Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

Show history

Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2026/2027 (N0613A140035) Computer Science UI P English Ostrava 1 Choice-compulsory type A study plan
2025/2026 (N0613A140035) Computer Science DZO P English Ostrava 1 Choice-compulsory type A study plan
2025/2026 (N0716A060002) Automotive Electronic Systems P English Ostrava 1 Compulsory study plan
2024/2025 (N0613A140035) Computer Science DZO P English Ostrava 1 Choice-compulsory type A study plan
2024/2025 (N0688A140015) Industry 4.0 AZD P English Ostrava 1 Compulsory study plan
2024/2025 (N0716A060002) Automotive Electronic Systems P English Ostrava 1 Compulsory study plan
2024/2025 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 1 Optional study plan
2024/2025 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 1 Optional study plan
2023/2024 (N0688A140015) Industry 4.0 AZD P English Ostrava 1 Compulsory study plan
2023/2024 (N0613A140035) Computer Science DZO P English Ostrava 1 Choice-compulsory type A study plan
2023/2024 (N0716A060002) Automotive Electronic Systems P English Ostrava 1 Compulsory study plan
2023/2024 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 1 Optional study plan
2023/2024 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 1 Optional study plan
2023/2024 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2023/2024 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2022/2023 (N0613A140035) Computer Science DZO P English Ostrava 1 Choice-compulsory type A study plan
2022/2023 (N0688A140015) Industry 4.0 AZD P English Ostrava 1 Compulsory study plan
2022/2023 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 1 Optional study plan
2022/2023 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 1 Optional study plan
2022/2023 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2022/2023 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2021/2022 (N0688A140015) Industry 4.0 AZD P English Ostrava 1 Compulsory study plan
2021/2022 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 1 Optional study plan
2021/2022 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 1 Optional study plan
2021/2022 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2021/2022 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2021/2022 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2020/2021 (N0688A140015) Industry 4.0 AZD P English Ostrava 1 Compulsory study plan
2020/2021 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2020/2021 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2020/2021 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2020/2021 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 1 Optional study plan
2020/2021 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 1 Optional study plan
2019/2020 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2019/2020 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2019/2020 (N2647) Information and Communication Technology (1103T031) Computational Mathematics K English Ostrava 1 Optional study plan
2019/2020 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Choice-compulsory study plan
2019/2020 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2019/2020 (N0541A170008) Computational and Applied Mathematics (S01) Applied Mathematics P English Ostrava 1 Compulsory study plan
2019/2020 (N0541A170008) Computational and Applied Mathematics (S02) Computational Methods and HPC P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2018/2019 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (1103T031) Computational Mathematics K English Ostrava 1 Optional study plan
2018/2019 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Choice-compulsory study plan
2018/2019 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (1103T031) Computational Mathematics K English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Choice-compulsory study plan
2017/2018 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2017/2018 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (1103T031) Computational Mathematics K English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Choice-compulsory study plan
2016/2017 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2016/2017 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (1103T031) Computational Mathematics P English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (1103T031) Computational Mathematics K English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology P English Ostrava 1 Choice-compulsory study plan
2015/2016 (N2647) Information and Communication Technology (2612T025) Computer Science and Technology K English Ostrava 1 Choice-compulsory study plan
2015/2016 (N2647) Information and Communication Technology (2612T059) Mobile Technology P English Ostrava 1 Optional study plan
2015/2016 (N2647) Information and Communication Technology (2612T059) Mobile Technology K English Ostrava 1 Optional study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
ECTS - mgr. 2025/2026 Full-time English Optional 401 - Study Office stu. block
ECTS - mgr. 2024/2025 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2023/2024 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2022/2023 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2021/2022 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2020/2021 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2019/2020 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2018/2019 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2017/2018 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2016/2017 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2015/2016 Full-time English Optional 401 - Study Office stu. block

Assessment of instruction

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