Information Package / Course Catalogue
Digital Image Processing
Course Code: ZTM546
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

The aim of this course is to teach Image Segmentation, Recognition, Compression, Image Enhancement and Image Understanding techniques.

Course Content

Fundamentals of Image Processing and MATLAB, Intensity Transformations and Spatial Filtering, Frequency Domain Processing, Image Restoration, Quantization, Color Image Processing, Wavelets and Multi-Resolution Processing, Image Compression, Morphological Image Processing, Image Segmentation, Representation and Description, Object Recognition.

Name of Lecturer(s)
Lec. Yüksel AYDOĞAN
Learning Outcomes
1.To develop Image Processing Software; To have ability to apply segmentation, image analysis and recognition techniques on images in real life.
2.To gain the ability to recognize and use image processing environments and tools such as Matlab and C #.
3.To do research in state-of-the-art subjects of digital image processing area; preparing and doing presentation. To gain experience in reading and writing papers in DIP.
4.To learn basic concepts of Digital Image Processing (DIP), mathematical and software background; to have ability to apply DIP to problems. To recognize the role of DIP in computer engineering and computer science.
5.To gain the ability to apply image processing in the agricultural field.
Recommended or Required Reading
1.Image Processing. Analysis and Machine Vision (Fourth Edition), Milan Sonka, Vaclav Hlavac, Roger Boyle, Cengage Learning, 2014.
2.Digital Image Processing Using Matlab, 2nd Edition, by R. Gonzalez, R. Woods and S. Eddins, 2009, Prentice Hall.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Image Processing: Definition of Image. Definition of Image Processing. Aims, Importance and Limits of Image Processing. Study, Research and Application Areas of Image Processing
Week 2 - Theoretical
Matlab and DIP In Matlab
Week 3 - Theoretical
Image Sources (Gamma Ray, X-Ray, Ultraviolet, Visible and Infrared, Microwave, Radio, …). Components of an Image Processing System.
Week 4 - Theoretical
Digital Image Fundamentals.
Week 5 - Theoretical
Intensity Transformations and Spatial Filtering
Week 6 - Theoretical
Biometrics Recognition: Face Recognition, Character Recognition, Recognition Using Matlab Filtering in the Frequency Domain and Image Restoration
Week 7 - Theoretical
Morphological Image Processing Color Image Processing, Image Compression
Week 8 - Theoretical
Morphological Image Processing Color Image Processing, Image Compression
Week 9 - Theoretical
Image Segmentation
Week 10 - Theoretical
Representation, Description and Recognition
Week 11 - Theoretical
Geometric Transformations
Week 12 - Theoretical
Blur Algorithms
Week 13 - Theoretical
Image Sharpening Algorithms
Week 14 - Theoretical
Edge Detection Algorithms, Arithmetic and Logic Operators
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory1453112
Assignment45540
Laboratory42216
Midterm Examination114216
Final Examination114216
TOTAL WORKLOAD (hours)200
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
5
5
5
5
4
4
4
5
5
OÇ-2
3
4
4
4
3
4
OÇ-3
4
5
5
5
4
4
4
4
OÇ-4
4
4
3
3
4
OÇ-5
5
5
5
5
5
5
5
Adnan Menderes University - Information Package / Course Catalogue
2026