Computer Vision
Master
Bachelor
Course Information
- Learning Method: Lecture with integrated Practice
- Form of Exam: Oral
- Professor:
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Workload:
- Attendance: 48 hours
- Self Study: 132 hours
- Link:Hs-Kl.de
Computer Vision
The students understand the process of image creation by digital cameras and are able to perform camera calibration. They are capable of selecting and applying suitable algorithms to improve image quality. They are familiar with methods for pattern recognition in images and can apply them. They have developed an understanding of both classical and AI-based image segmentation and can select and use appropriate methods to solve concrete computer vision problems.
Content
The lecture covers the fundamentals of Computer Vision:
- Image formation and optics
- Camera model and calibration
- Fourier and wavelet transforms
- Image compression
- Convolution and pattern recognition
- Filter functions
- Image segmentation
- Industrial applications of machine vision