Image Processing with MATLAB and AI: Unterschied zwischen den Versionen
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| (4 dazwischenliegende Versionen desselben Benutzers werden nicht angezeigt) | |||
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# Solve the Image Processing Tasks with classic algorithms. | # Solve the Image Processing Tasks with classic algorithms. | ||
# Research on AI Solutions. | # Research on AI Solutions. | ||
# Evaluation of the solutions using a morphological box ([https://en.wikipedia.org/wiki/Morphological_box Zwicky box]) | |||
# Solve the Image Processing Tasks with AI algorithms. | # Solve the Image Processing Tasks with AI algorithms. | ||
# Compare the | # Compare the different approaches according to scientific criteria | ||
# | # Scientific documentation | ||
= Getting startes = | = Getting startes = | ||
* You are invited to the image processing class in [https://grader.mathworks.com/courses/169570-image-processing-with-matlab MATLAB Grader]. | * You are invited to the image processing class in [https://grader.mathworks.com/courses/169570-image-processing-with-matlab MATLAB Grader]. | ||
* Choose the examples from the categories in table 1. | * Choose the examples from the categories in table 1. Start with 1 end with 6. | ||
* Solve the tasks with classic algorithms. | * Solve the tasks with classic algorithms. | ||
* Solve the tasks with AI. | * Solve the tasks with AI. | ||
* Save your results in SVN. | * Save your results in SVN. | ||
* Use MATLAB R2025b for the algorithms. | |||
{| class="wikitable" | {| class="wikitable" | ||
|+ Table 1: Image Processing Categories | |+ Table 1: Image Processing Categories | ||
Aktuelle Version vom 17. Dezember 2025, 12:55 Uhr
| Autor: | Ajay Paul |
| Art: | bachelor thesis |
| Starttermin: | TBD |
| Abgabetermin: | TBD |
| Betreuer: | Prof. Dr.-Ing. Schneider |
Introduction
Signal processing has long been a basis in the analysis and manipulation of data in various domains such as telecommunications, radar, audio processing, and imaging. Signal processing has traditionally focused on analyzing, filtering, and interpreting signals in both the time and frequency domains. With the integration of AI, especially deep learning, the possibilities expand to include noise reduction and more. It is essential in many modern applications such as communications, audio and image processing, biomedical signal analysis, and control systems.
Task list
- Solve the Image Processing Tasks with classic algorithms.
- Research on AI Solutions.
- Evaluation of the solutions using a morphological box (Zwicky box)
- Solve the Image Processing Tasks with AI algorithms.
- Compare the different approaches according to scientific criteria
- Scientific documentation
Getting startes
- You are invited to the image processing class in MATLAB Grader.
- Choose the examples from the categories in table 1. Start with 1 end with 6.
- Solve the tasks with classic algorithms.
- Solve the tasks with AI.
- Save your results in SVN.
- Use MATLAB R2025b for the algorithms.
| # | Categorie | Grader Lecture |
|---|---|---|
| 1 | Recovery and restoration of information | 5 |
| 2 | Image enhancement | 6 |
| 3 | Noise Reduction | 7 |
| 4 | Data based segmentation | 8 |
| 5 | Model based segmentation | 9 |
| 6 | Classification | 10 |
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