Differential Geometric Aspects of Image Processing Winter Term 2019 |
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Differential Geometric Aspects of Image Processing
Lectures (3h) with exercises (1h), winter term 2019
Specialised course in mathematical image analysis,
suitable for students in mathematics and computer science programs. Entrance requirements – Contents – References – Undergraduate knowledge of mathematics. Students should be familiar with basic concepts of multivariate calculus and linear algebra as covered in introductory maths course. Mathematical prerequisites which exceed the basic mathematics courses are provided within the lecture. Previous knowledge in either digital image processing or differential geometry is therefore helpful but not required. The course is concerned with modern methods of digital image processing which rely on the differential geometry of curves and surfaces. This includes methods of image enhancement (like smoothing procedures) as well as feature extraction and segmentation (like locating contours using active contour models). The lecture aims at combining theoretical foundation directly with a variety of applications from the above-mentioned fields; the range of topics extends up to recent research problems. An introduction to the relevant concepts and results from differential geometry will be included in the course. Topics include:
The homework assignments are intended to be solved at home and have to be
submitted in the lecture break of the following Thursday.
In order to qualify for the exam
you must obtain 50% of the possible points on average.
Please do not forget to bring your student ID card with you.
Participants of the course can download the lecture materials here
(access password-protected):
Slides of the lecture
Classroom Exercises
Homework Exercises
References for topological and differential geometric foundations:
Further references will be given during the lecture. |
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