## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2021

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).

Taught online. **Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Thu 14:00–15:50 Virtuální místnost
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**7**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 52 fields of study the course is directly associated with, display
**Course objectives**- The objective of the course is to introduce mathematical morphology theory, algorithms, and applications to students interested in digital image processing.
**Learning outcomes**- At the end of the course students should be able to: understand and explain the principles of mathematical morphology methods and efficient algorithms for their computation; respect their properties and theoretical limits; demonstrate their usage on typical image analysis problems in various application fields; solve image analysis problems using mathematical morphology.
**Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class exercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically eight open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2022

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).

Taught online. **Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Prerequisites**- Knowledge at the level of course PB130 Introduction to Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**0**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 52 fields of study the course is directly associated with, display
**Course objectives**- The objective of the course is to introduce mathematical morphology theory, algorithms, and applications to students interested in digital image processing.
**Learning outcomes**- At the end of the course students should be able to: understand and explain the principles of mathematical morphology methods and efficient algorithms for their computation; respect their properties and theoretical limits; demonstrate their usage on typical image analysis problems in various application fields; solve image analysis problems using mathematical morphology.
**Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class exercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically eight open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- The course is taught annually.

The course is taught: every week.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2020

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)

Mgr. Jan Ježek (assistant) **Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Mon 17. 2. to Fri 15. 5. Tue 10:00–11:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**3**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 52 fields of study the course is directly associated with, display
**Course objectives**- The objective of the course is to introduce mathematical morphology theory, algorithms, and applications to students interested in digital image processing.
**Learning outcomes**- At the end of the course students should be able to: understand and explain the principles of mathematical morphology methods and efficient algorithms for their computation; respect their properties and theoretical limits; demonstrate their usage on typical image analysis problems in various application fields; solve image analysis problems using mathematical morphology.
**Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class exercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically eight open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2018

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Thu 12:00–13:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**4**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 23 fields of study the course is directly associated with, display
**Course objectives****Learning outcomes****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class excercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically 8 open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2017

**Extent and Intensity**- 2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Tue 10:00–11:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**1**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 23 fields of study the course is directly associated with, display
**Course objectives****Learning outcomes****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class excercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically 8 open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2016

**Extent and Intensity****Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)

Mgr. Jan Ježek (assistant) **Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Thu 16:00–17:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**0**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 23 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Attendance at class excercises required, written as well as oral examination. In the written part, 55 points can be obtained by presenting correct results of morphological transforms on given 1D functions, and 45 points in typically 8 open-style questions. To continue to the oral part, the students must achieve at least 50 points from the written part. The oral part is a discussion about the written part testing understanding the main concepts.
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2015

**Extent and Intensity**- 2/2. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Thu 14:00–15:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.

The capacity limit for the course is 24 student(s).

Current registration and enrolment status: enrolled:**0**/24, only registered:**0**/24, only registered with preference (fields directly associated with the programme):**0**/24 **fields of study / plans the course is directly associated with**- there are 23 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods****Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2014

**Extent and Intensity**- 2/2. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Tue 8:00–9:50 B411, Tue 12:00–13:50 B311
**Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**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**- there are 22 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods****Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2013

**Extent and Intensity**- 2/2. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- doc. RNDr. Petr Matula, Ph.D.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Thu 8:00–9:50 B411
- Timetable of Seminar Groups:

*P. Matula* **Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**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**- there are 22 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

*recommended literature*- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods****Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2012

**Extent and Intensity****Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D.

Supplier department: Department of Visual Computing - Faculty of Informatics **Timetable**- Mon 12:00–13:50 B411, Mon 14:00–15:50 B311
**Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**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**- there are 22 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Written as well as oral examination. Attendance at class excercises required. Study materials in English. Teaching in English or Czech (in the case of all enrolled students prefer Czech)
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2011

**Extent and Intensity****Teacher(s)**- doc. RNDr. Pavel Matula, Ph.D. (lecturer)
**Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D. **Timetable**- Tue 10:00–11:50 B311, Wed 8:00–9:50 C416
**Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations****fields of study / plans the course is directly associated with**- there are 22 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Written as well as oral examination. Attendance at class excercises required. Study materials in English. Teaching in English or Czech (in the case of all enrolled students prefer Czech)
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2010

**Extent and Intensity**- 2/2. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D. **Timetable**- Tue 8:00–9:50 B411, Tue 10:00–11:50 B311
**Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations****fields of study / plans the course is directly associated with**- there are 22 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods**- Written as well as oral examination. Attendance at class excercises required. Study materials in English. Teaching in English or Czech (in the case of all enrolled students prefer Czech)
**Language of instruction**- English
**Further Comments**- Study Materials

The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Autumn 2009

**Extent and Intensity**- 2/2. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D. **Timetable**- Tue 12:00–13:50 C511, Tue 16:00–17:50 B311, Tue 18:00–19:50 B311
**Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations****fields of study / plans the course is directly associated with**- there are 22 fields of study the course is directly associated with, display
**Course objectives****Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers, hierarchical segmentation
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Teaching methods**- Lectures followed by class exercises in a computer room to gain hands-on experience.
**Assessment methods****Language of instruction**- English
**Further Comments**- The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2009

**Extent and Intensity**- 2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)
**Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D. **Timetable**- Mon 11:00–11:50 B311, Mon 12:00–13:50 C416
**Prerequisites**- Knowledge at the level of course PV131 Digital Image Processing is useful.
**Course Enrolment Limitations****fields of study / plans the course is directly associated with**- there are 18 fields of study the course is directly associated with, display
**Course objectives**- The lecture is focused on mathematical morphology in image analysis. The methods will be discussed from theoretical, application and algorithmic point of view. Students can try the methods on simple practical examples in class exercises.
**Syllabus**- Structuring element and its decomposition
- Fundamental morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Hit-or-miss transform, skeletons, thinning, thickening
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers
- Efficient implementation of morphological operators
- Granulometry, classification, texture analysis

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Assessment methods****Language of instruction**- English
**Further Comments**- The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2008

**Extent and Intensity**- 2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
**Teacher(s)**- doc. RNDr. Pavel Matula, Ph.D. (lecturer)
**Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D. **Timetable**- Wed 15:00–15:50 B311, Wed 16:00–17:50 B410
**Prerequisites**- Knowledge at the level of the lecture PA170 is assumed.
**Course Enrolment Limitations****fields of study / plans the course is directly associated with**- there are 18 fields of study the course is directly associated with, display
**Course objectives**- The lecture is focused on mathematical morphology in image analysis. The methods will be discussed from theoretical, application and algorithmic point of view. Students can try the methods on simple practical examples.
**Syllabus**- Structuring element and its decomposition
- Basic morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Granulometry
- Hit-or-miss transform, skeletons
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers
- Efficient implementation of morphological operators

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Assessment methods**(in Czech)- Písemná zkouška, nutná účast na cvičeních a domácí práce.
**Language of instruction**- English
**Further Comments**- The course is taught annually.

## PA173 Mathematical Morphology

**Faculty of Informatics**

Spring 2007

The course is not taught in Spring 2007

**Extent and Intensity**- 2/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
**Teacher(s)**- doc. RNDr. Petr Matula, Ph.D. (lecturer)

doc. RNDr. Pavel Matula, Ph.D. (lecturer) **Guaranteed by**- prof. Ing. Jiří Sochor, CSc.

Department of Visual Computing - Faculty of Informatics

Contact Person: doc. RNDr. Petr Matula, Ph.D. **Prerequisites**-
**PA170**Digital Geometry

Knowledge at the level of the lecture PA170 is assumed. **Course Enrolment Limitations****fields of study / plans the course is directly associated with**- Applied Informatics (programme FI, N-AP)
- Informatics (programme FI, N-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)

**Course objectives**- The lecture is focused on mathematical morphology in image analysis. The methods will be discussed from theoretical, application and algorithmic point of view. Students can try the methods on simple practical examples.
**Syllabus**- Structuring element and its decomposition
- Basic morphological operators (erosion, dilation, opening, closing, top-hat, ...)
- Granulometry
- Hit-or-miss transform, skeletons
- Geodesic transformations and metrics
- Morphological reconstructions
- Morphological filters
- Segmentation, watershed transform, markers
- Efficient implementation of morphological operators

**Literature**- SOILLE, Pierre.
*Morphological Image Analysis: Principles and Applications*. 2nd edition. Berlin: Springer-Verlag, 2003. ISBN 3-540-42988-3. info

- SOILLE, Pierre.
**Assessment methods**(in Czech)- Písemná zkouška, nutná účast na cvičeních a domácí práce.
**Language of instruction**- Czech
**Further Comments**- The course is taught annually.

The course is taught: every week.

- Enrolment Statistics (recent)