Digital Image Processing (EE421) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Digital Image Processing EE421 Area Elective 2 2 0 3 5
Pre-requisite Course(s)
MATH275
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Experiment, Question and Answer, Drill and Practice, Team/Group, Brain Storming.
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Hakan Tora
Course Assistants
Course Objectives •Study the image fundamentals and mathematical transforms necessary for image processing. •Study the image enhancement techniques •Study image restoration procedures. •Study the image compression procedures. •Study the image segmentation and representation techniques
Course Learning Outcomes The students who succeeded in this course;
  • Understand the basic concepts of digital image processing such as 2D data representation, color image representation, 2D sampling and quantization, and 2D filtering
  • Understand the basic theory of transforms and learn the properties and use of different types of transforms
  • Learn the basics of different image processing methods such as image enhancement, image filtering and restoration, image analysis, image compression
  • Propose methods to solve image processing problems
  • Ability to complete a term project
Course Content 2-D systems and transforms, image acquisition, sampling and quantization, linear and non-linear techniques for image enhancement and restoration and image compression, differential pulse code modulation, vector quantization, wavelets, subband coding, still and video compression coding standards.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Digital Image Fundamentals and Transforms Glance this week’s topics from the lecture
2 Image Enhancement in the Spatial Domain •Gray Level Transformations •Histogram Processing •Spatial Filtering Review last week and glance this week’s topics from the lecture
3 Image Enhancement in the Spatial Domain •Smoothing Spatial Filters •Sharpening Spatial Filters Review last week and glance this week’s topics from the lecture
4 Image Enhancement in the Frequency Domain •Fourier Transform and Frequency Domain •Smoothing Frequency Domain Filters •Sharpening Frequency Domain Filters Review last week and glance this week’s topics from the lecture
5 Image Enhancement in the Frequency Domain •Homomorphic Filtering •Implementation Review last week and glance this week’s topics from the lecture
6 Image Restoration Techniques •Degradation Model •Inverse Filtering •Wiener Filtering Glance this week’s topics from the lecture
7 Image Restoration Techniques Review last week and glance this week’s topics from the lecture
8 Image Segmentation •Detection of Discontinuities •Edge Linking and Boundary Detection •Thresholding Glance this week’s topics from the lecture
9 Image Segmentation •Region Based Segmentation •The use motion in Segmentation Review last week and glance this week’s topics from the lecture
10 Image Compression •Image Compression Models •Elements of Information Theory •Error-Free Compression •Lossy Compression •Image Compression Standards Glance this week’s topics from the lecture
11 Morphological Image Processing •Dilation and Erosion •Opening And Closing •Morphological Algorithms Glance this week’s topics from the lecture
12 Representation and Description •Representation •Boundary Descriptors •Regional Descriptors Glance this week’s topics from the lecture
13 Representation and Description •Use of Principle of Components for Description Review last week and glance this week’s topics from the lecture
14 Object Recognition •Patterns and Pattern Classes •Matching, Optimum Statistical Classifiers Glance this week’s topics from the lecture
15 Final examination period Review topics
16 Final examination period Review topics

Sources

Course Book 1. Digital Image Processing,2nd Edition, Rafael C. Gonzales and Richard E. Woods, Pearson Education, 2003.
Other Sources 2. Two-Dimensional Signal and Image Processing, Jae S. Lim, Prentice-Hall, 1989.
3. Digital Video Processing, A. Murat Tekalp, Prentice-Hall, 1995.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory 9 15
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project 1 15
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 40
Final Exam/Final Jury 1 30
Toplam 12 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge of subjects related to mathematics, natural sciences, and Electrical and Electronics Engineering discipline; ability to apply theoretical and applied knowledge in those fields to the solution of complex engineering problems. X
2 An ability to identify, formulate, and solve complex engineering problems, ability to choose and apply appropriate models and analysis methods for this. X
3 An ability to design a system, component, or process under realistic constraints to meet desired needs, and ability to apply modern design approaches for this. X
4 The ability to select and use the necessary modern techniques and tools for the analysis and solution of complex problems encountered in engineering applications; the ability to use information technologies effectively X
5 Ability to design and conduct experiments, collect data, analyze and interpret results for investigating complex engineering problems or discipline-specific research topics. X
6 An ability to function on multi-disciplinary teams, and ability of individual working. X
7 Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; active report writing and understanding written reports, preparing design and production reports, the ability to make effective presentation the ability to give and receive clear and understandable instructions. X
8 Awareness of the necessity of lifelong learning; the ability to access knowledge, follow the developments in science and technology and continuously stay updated. X
9 Acting compliant with ethical principles, professional and ethical responsibility, and knowledge of standards used in engineering applications. X
10 Knowledge about professional activities in business, such as project management, risk management, and change management awareness of entrepreneurship and innovation; knowledge about sustainable development. X
11 Knowledge about the impacts of engineering practices in universal and societal dimensions on health, environment, and safety. the problems of the current age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory 6 2 12
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration 2 2 4
Project 1 20 20
Report
Homework Assignments 7 2 14
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 2 4
Prepration of Final Exams/Final Jury 1 2 2
Total Workload 132