Digital Image Processing (EE421) Ders Detayları

Course Name Corse Code Dönemi Lecture Hours Uygulama Saati Lab Hours Credit ECTS
Digital Image Processing EE421 Elective Courses 2 2 0 3 5
Pre-requisite Course(s)
MATH 275
Course Language İngilizce
Course Type Technical Elective Courses
Course Level Lisans
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
Major Area Courses X
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 Accumulated knowledge on mathematics, science and mechatronics engineering; an ability to apply the theoretical and applied knowledge of mathematics, science and mechatronics engineering to model and analyze mechatronics engineering problems. X
2 An ability to differentiate, identify, formulate, and solve complex engineering problems; an ability to select and implement proper analysis, modeling and implementation techniques for the identified engineering problems. X
3 An ability to design a complex system, product, component or process to meet the requirements under realistic constraints and conditions; an ability to apply contemporary design methodologies; an ability to implement effective engineering creativity techniques in mechatronics engineering. (Realistic constraints and conditions may include economics, environment, sustainability, producibility, ethics, human health, social and political problems.) X
4 An ability to develop, select and use modern techniques, skills and tools for application of mechatronics engineering and robot technologies; an ability to use information and communications technologies effectively. X
5 An ability to design experiments, perform experiments, collect and analyze data and assess the results for investigated problems on mechatronics engineering and robot technologies. X
6 An ability to work effectively on single disciplinary and multi-disciplinary teams; an ability for individual work; ability to communicate and collaborate/cooperate effectively with other disciplines and scientific/engineering domains or working areas, ability to work with other disciplines. X
7 An ability to express creative and original concepts and ideas effectively in Turkish and English language, oral and written, and technical drawings. X
8 An ability to reach information on different subjects required by the wide spectrum of applications of mechatronics engineering, criticize, assess and improve the knowledge-base; consciousness on the necessity of improvement and sustainability as a result of life-long learning; monitoring the developments on science and technology; awareness on entrepreneurship, innovative and sustainable development and ability for continuous renovation. X
9 Consciousness on professional and ethical responsibility, competency on improving professional consciousness and contributing to the improvement of profession itself. X
10 A knowledge on the applications at business life such as project management, risk management and change management and competency on planning, managing and leadership activities on the development of capabilities of workers who are under his/her responsibility working around a project. X
11 Knowledge about the global, societal and individual effects of mechatronics engineering applications on the human health, environment and security and cultural values and problems of the era; consciousness on these issues; awareness of legal results of engineering solutions. X
12 Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions. X
13 Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planing, improving or changing the norms with a criticism. 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