UIN3057 Computer Vision

Faculty of Philosophy and Science in Opava
Summer 2022
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ing. Jiří Blahuta, Ph.D. (lecturer)
RNDr. Jiří Martinů, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Petr Čermák, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Timetable
Tue 9:45–11:20 LEI
  • Timetable of Seminar Groups:
UIN3057/A: Tue 14:45–16:20 LEI, J. Martinů
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Computer Vision is a course which is closely related with robotics and image analysis. The course is focused on successful analysis of input image followed by desired reaction. During the course are discussed practical applications of the mostly used computer vision algorithms in C#, C++ and also in MATLAB with Image Processing Toolbox.
Syllabus
  • 1. Image pre-processing. Practical implementation of the following algorithms:
    a. conversion color 24bit RGB image into 8bit grayscale (C#), different approaches
    b. convolution filters demos, e.g. edge detection, edge enhancing, blur, sharpening, relief and other filters
    2. Segmentation and feature recognition. Practical implementation:
    a. Quadtree decomposition (C#)
    b. Global thresholding (C#)
    c. Line finding (C#)
    3. Reverse stereoprojection, camera model, two cameras case, absolute and relative calibration and reconstruction
    4. Analysis of time-variant images by Discrete Kalman Filter
    5. Objects tracking in images from moving camera
    6. Motion detection, image substraction methods
    7. Environment model estimation
    8. Optical flow. Practical implementation of the following algorithms:
    a. Lucas-Kanade algorithm to motion detection (MATLAB)
    9. Interest point detection, SURF/SIFT method comparison (C++)
Literature
    required literature
  • Haralick Shapiro. Computer vision. New York. info
  • SOJKA, E. Zpracování digitálního obrazu. 2000. ISBN 80-7078-746-5. info
  • HARALICK, R. M. , SHAPIRO, L. G. Computer and Robot Vision. New York, 1992. info
    recommended literature
  • Čermák, P., Blahuta, J., Martinu, J. Počítačové vidění. Opava, 2013. URL info
  • SZELISKI, Richard. Computer Vision: Algorithms and Applications. Berlin, 2010. info
  • DOUGHERTY, G. Digital Image Processing for Medical Applications. Oxford, 2009. ISBN 978-0521860857. info
  • ŽÁRA, Jiří, SOCHOR, Jiří, FELKEL, Petr, BENEŠ, Bedřich. Moderní počítačová grafika. Brno, 2005. ISBN 978-80-2510-454-5. info
  • SCHLESINGER, M.I., HLAVÁČ, V. Deset přednášek z teorie statistického a strukturního rozpoznávání. Praha, 1999. info
  • ŠONKA, M., HLAVÁČ, V., BOYLE, R. Image Processing, Analysis and Machine Vision. Boston, 1998. info
  • PRATT, W. K. Digital Image Processing, Second Edition. New York, 1991. info
Teaching methods
Interactive lecture
Lecture with a video analysis
Assessment methods
Exam
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
Teacher's information
* 75% attendance in the lecture and exercises, active participation
* written test in the extent of the given literature and the content of seminars - success rate 50% of 30 points
* implementation of selected methods of computer vision on selected robot, success rate 50% of 30 points from programming and 10 points from documentation
* 40 points exam, sucess rate 50%
The course is also listed under the following terms Summer 1994, Summer 1995, Summer 1996, Summer 1997, Summer 1998, Summer 1999, Summer 2000, Summer 2001, Summer 2002, Summer 2003, Summer 2004, Summer 2005, Summer 2006, Summer 2007, Summer 2008, Summer 2009, Summer 2010, Summer 2011, Summer 2012, Summer 2013, Summer 2014, Summer 2015, Summer 2016, Summer 2017, Summer 2018, Summer 2019, Summer 2020, Summer 2021, Summer 2023, Summer 2024, Summer 2025.
  • Enrolment Statistics (Summer 2022, recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2022/UIN3057