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Course info
KKY / ZDO-E
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Course description
Department/Unit / Abbreviation
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KKY
/
ZDO-E
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Digital Image Processing
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
6
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
3
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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No
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Included in study average
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YES
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Language of instruction
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English
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / -
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0 / -
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4 / -
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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2 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter + Summer
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Semester taught
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Winter + Summer
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Minimum (B + C) students
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not determined
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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English
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
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Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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KKY/ZDO
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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Understand to the principles of digital image processing and computer vision. Analyze of image information properties and interpret of such information, design and create of an algorithm for processing of image information with the aim of recognition of objects, phenomena, or scene properties contained in image.
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Requirements on student
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active presence at seminars
project in teams of max 2, project defense,
oral exam
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Content
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Definition of the digital image processing task, digitization of image information, representation of colour information. Pre-processign methods - point brightness transformations, geometric transformations, noise filtration, greadient operators, frequency analysis. Morphologic tranformations. Methods of segmentation. Methods of description of objects - description based on region boundaries, description based on shape of regions. Classification. Motion analysis. 3D imaging. Applications in photography, industry, human-computer communication, and medicine.
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
Doc. Ing. Miloš Železný, Ph.D. ,
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Lecturer:
Ing. Ivan Gruber, Ph.D. (100%),
Ing. Miroslav Jiřík, Ph.D. (100%),
Ing. Zdeněk Krňoul, Ph.D. (100%),
Doc. Ing. Miloš Železný, Ph.D. (100%),
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Tutorial lecturer:
Ing. Miroslav Jiřík, Ph.D. (100%),
Doc. Ing. Miloš Železný, Ph.D. (100%),
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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39
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Practical training (number of hours)
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26
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Preparation for an examination (30-60)
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58
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Preparation for laboratory testing; outcome analysis (1-8)
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8
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Team project (50/number of students)
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25
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Total
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156
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
have basic knowledge of linear algebra and matrix calculation |
have basic knowledge of mathematical analysis |
have basic knowledge of a theory of probability and mathematical statistics |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
analyse and interpret information |
develop an algorithm and implement a task |
evaluate obtained results |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
have a knowledge of digital image processing |
be able to explain basic principles of image pre-processing |
be able to explain the methods of the object description and classification |
Skills - skills resulting from the course: |
be able to solve the image processing tasks |
be able to apply methods of computer processing of image information |
choose correct method for the image processing task |
Competences - competences resulting from the course: |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Seminar work |
Continuous assessment |
Oral exam |
Skills - skills achieved by taking this course are verified by the following means: |
Seminar work |
Continuous assessment |
Skills demonstration during practicum |
Competences - competence achieved by taking this course are verified by the following means: |
Seminar work |
Continuous assessment |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Self-study of literature |
Individual study |
Skills - the following training methods are used to achieve the required skills: |
Practicum |
Lecture with visual aids |
Project-based instruction |
Competences - the following training methods are used to achieve the required competences: |
Project-based instruction |
Practicum |
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