Digital Image Processing
| Title | ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ / Digital Image Processing |
| Code | ΠΡ02 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Ioannis Pitas |
| Common | No |
| Status | Active |
| Course ID | 40002287 |
| Academic Year | 2017 – 2018 |
| Class Period | Winter |
| Faculty Instructors | |
| Class ID | 600112955
|
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600112955
- At the Website of the School: http://pileas.csd.auth.gr/course/view.php?id=57
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=8154
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge in applied mathematics and digital signal processing. Programming skills. Good level of English.
Learning Outcomes
a) Knowledge: Familiarization with the fundamental digital image processing principles and algorithms, such as the theory and technology of image digitization, processing, analysis, compression/storage, and shape description. Exposure to digital image processing programming using C/C++ and MATLAB. Acquaintance with digital image processing systems and their application in areas, such as with applications in medicine/biology, remote sensing/GIS, image communication and www applications, image printing/display, etc.
b) Skills: Setting the foundations for advanced studies on digital image processing issues and applications. Acquisition of skills in the use and development of digital image processing algorithms. Promoting analytical and programming skills. Ability to develop basic digital image processing applications using C/C++ and MATLAB.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
Course Content (Syllabus)
Digital image recording/digitization. Image enhancement and filtering. Image restoration. Digital image compression and related standards (e.g. JPEG/JPEG2000) . Edge detection algorithms. Image segmentation. Shape description. Programming assignments in C/C++ and MATLAB.
Educational Material Types
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 114 | 3.8 | ✓ | ✓ | |
| Project | 21 | 0.7 | ✓ | ||
| Exams | 15 | 0.5 | ✓ | ||
| Total | 150 | 5 |
Student Assessment
Description
Written exams. Literature survey or programming assignments or mid-term exams or oral presentations provide an additional 2-4 points, if the exam mark is at least 4.
Student Assessment methods
- Written Exam with Short Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Πήτας Ι. «Ψηφιακή Επεξεργασία Εικόνας», Θεσσαλονίκη, 2010.
Παπαμάρκος Ν. «Ψηφιακή Επεξεργασία και Ανάλυση Εικόνας», Εκδόσεις Ν. Παπαμαρκος, Αθήνα, 2010.
Additional bibliography for study
I. Pitas, "Digital Image Processing Algorithms and Aplications", Wiley Inter-Science, 2000.
William K. Pratt,"Digital image processing", John Wiley & Sons, 2007 3) R. C. Gonzalez, R.E. Woods,"Digital image processing", Addison-Welsey, 2007.
Last Update
03-06-2016
