Course Details

Course Code (English)*

Semester*

Title (English)*

Lecture Hours (Weekly)

ECTS Credits*

Course Type (English)

Prerequisites (English) -

Course URL (e.g., on e-class)

Learning Outcomes (English) - 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

General Competencies (English) - 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

Course Content (English) 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

Use of ICT (English) Lectures, powerpoint presentations, e-mail communication, in-person communication and problem solving, provision of implemented methods of digital image processing, provision of up-to-date relevant literature

Is it elective? Άγνωστο Ναι Όχι

Load within semester (Hours)

Lecture Hours

Lab Hours

Independent Study*

Project Work*

Lab Report*