Digital Image Processing and Applications
General
Code: ΕΠ10
Language: Greek
Delivery: Face-to-face
Prerequisites: -
Workload
- Lectures: 39.0 hours
- Lab: 0.0 hours
- Study: 46.0 hours
- Project: 40.0 hours
Course Content
Week 1: Introduction to the course
Week 2: Transformations
Week 3: Course lab (1)
Week 4: Optimization
Week 5: Segmentation
Week 6: Course lab (2)
Week 7: Edge detection
Week 8: Compression
Week 9: Course lab (3)
Week 10: Feature Extraction
Week 11: Multiscale analysis
Week 12: Course lab (4)
Week 13: Addressing questions for course assignments
Learning Outcomes
- Understanding of basic principles of capturing and processing digital images
- Understanding fundamental methodologies for image transformation
- Adoption of different optimization methods
- Analysis of spatial segmentation, compression and edge detection methods
- Understanding of basic methodologies for feature extraction and multiscale analysis
Skills
- Search, analysis and synthesis of data and information with the use of the assorted technologies
- Decision making
- Individual work
- Project design and management
- Promoting reasoning and self-improvement
- Promoting free, creative and deductive reasoning