Digital Image Processing

Course Information
TitleΨηφιακή Επεξεργασία Εικόνας / Digital Image Processing
SchoolElectrical and Computer Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorAnastasios Ntelopoulos
Course ID600001043

Programme of Study: Electrical and Computer Engineering

Registered students: 116
OrientationAttendance TypeSemesterYearECTS
ELECTRICAL ENERGYElective Courses845

Class Information
Academic Year2021 – 2022
Class PeriodSpring
Faculty Instructors
Weekly Hours4
Class ID
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
General Prerequisites
Linear Algebra, Probabilities, Signals and Systems theory, Stochastic Signals, Digital Signal Processing
Learning Outcomes
1. To understand the nature of images as information regarding colors and luminance. 2. To extend the mathematical tools used in 1D signal processing to the two dimensions. 3. To understand the problems that are handled by Digital Image Processing (Scene analysis, noise reduction, detection/recognition of objects, etc.) 4. To understand the theoretical aspects of tools (mathematical/algorithmic) used for the solution of the above problems. 5. To gain practical experience in the development of Digital Image Processing algorithms via simulation of selected image processing tools in 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
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
1. Image perception and acquisition – Luminosity and Colors. 2. Digitization (Sampling and Quantization) 3. Images as 2D signals 3.1 Fourier and z image transforms 3.2 Convolution, Convolution theorems 3.3 Filters 3.4 2D stochastic processes 4. Image analysis 4.1 Edge and salient point detection 4.2 Image segmentation 4.3 Image feature extraction 4.4 Shape and contour computation 5. Image Enhancement 5.1 Color enhancement 5.2 Noise reduction 5.3 inverse filtering, Wiener filter 6. Multirate analysis/synthesis
Educational Material Types
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
e-notes Implementation of homework assignments in Matlab Communication via eTHMMY portal
Course Organization
homework assignemnts: simulation of DIP components in Matlab210.7
Student Assessment
Evaluation is based on an intermediate examination, 3-4 homework assignments and the final examination
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
  • homework assignments for the simulation of DIP algorithms (Formative, Summative)
Course Bibliography (Eudoxus)
1. Ψηφιακή Επεξεργασία και Ανάλυση Εικόνας Κωδικός Βιβλίου στον Εύδοξο: 86 Έκδοση: 2/2010 Συγγραφείς: Παπαμάρκος Νικόλαος ISBN: 978-960-92731-3-8 Διαθέτης (Εκδότης): ΝΙΚΟΛΑΟΣ ΠΑΠΑΜΑΡΚΟΥ 2. Ψηφιακή Επεξεργασία Εικόνας Κωδικός Βιβλίου στον Εύδοξο: 8020 Έκδοση: 2/2010 Συγγραφείς: Ιωάννης Πήτας ISBN: 978-960-91564-3-1 Διαθέτης (Εκδότης): ΙΩΑΝΝΗΣ ΠΗΤΑΣ 3. Ψηφιακή Επεξεργασία Εικόνας Κωδικός Βιβλίου στον Εύδοξο: 18548692 Έκδοση: 3η έκδ./2010 Συγγραφείς: Gonzales ISBN: 978-960-418-255-8 Διαθέτης (Εκδότης): ΕΚΔΟΣΕΙΣ Α. ΤΖΙΟΛΑ & ΥΙΟΙ Α.Ε. 4. ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ & ΒΙΝΤΕΟ Κωδικός Βιβλίου στον Εύδοξο: 110 Έκδοση: 1/2010 Συγγραφείς: Ι. Ν. ΕΛΛΗΝΑΣ ISBN: 978-960-93-1836-5 Διαθέτης (Εκδότης): ΙΩΑΝΝΗΣ ΕΛΛΗΝΑΣ
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