Instıtute Of Graduate Educatıon
Informatıon Technologıes Master's Program (Wıthout Thesıs)
Course Information
| APPLIED GRAPHIC AND RECOGNITION TECHNIQUES | |||||
|---|---|---|---|---|---|
| Code | Semester | Theoretical | Practice | National Credit | ECTS Credit |
| Hour / Week | |||||
| IT564 | Fall | 3 | 0 | 3 | 6 |
| Prerequisites and co-requisites | None |
|---|---|
| Language of instruction | Turkish |
| Type | Elective |
| Level of Course | Master's |
| Lecturer | Asst. Prof. Dr. Mehmet Ali AKTAŞ |
| Mode of Delivery | Face to Face |
| Suggested Subject | None |
| Professional practise ( internship ) | None |
| Objectives of the Course | Objectives of this course are; to make the student identify image processing methods, comprehend importance of using computer in image processing, construct basic image implementations with MATLAB program packet and develop image processing algorithms. |
| Contents of the Course | Digital Image Fundamentals, Spatial Domain Processing, Frekans Domain Processing, Image Restoration, Image Segmentation, Wavelets, Image Compression |
Learning Outcomes of Course
| # | Learning Outcomes |
|---|---|
| 1 | Learning image processing |
| 2 | Removing noise from images |
| 3 | Filtering in frequency domain |
| 4 | Processing Black and White images |
| 5 | Ability to apply morphologic operations |
Course Syllabus
| # | Subjects | Teaching Methods and Technics |
|---|---|---|
| 1 | General introduction | Lecture, discussion, presentation |
| 2 | Introduction to digital image processing | Lecture, discussion, presentation |
| 3 | Digital image fundamentals | Lecture, discussion, presentation |
| 4 | Sampling and quantization | Lecture, discussion, presentation |
| 5 | Image enhancement | Lecture, discussion, presentation |
| 6 | Image enhancement | Lecture, discussion, presentation |
| 7 | 1. Mid Term Exam | Exam |
| 8 | Histogram processing | Lecture, discussion, presentation |
| 9 | Histogram processing | Lecture, discussion, presentation |
| 10 | Filters | Lecture, discussion, presentation |
| 11 | The Fourier transform and the frequency Domain | Lecture, discussion, presentation |
| 12 | Noise models | Lecture, discussion, presentation |
| 13 | Black and white image processing | Lecture, discussion, presentation |
| 14 | Final Exam | Exam |
| 15 | ||
| 16 |
Course Syllabus
| # | Material / Resources | Information About Resources | Reference / Recommended Resources |
|---|
Method of Assessment
| # | Weight | Work Type | Work Title |
|---|---|---|---|
| 1 | 40% | Mid-Term Exam | Mid-Term Exam |
| 2 | 60% | Final Exam | Final Exam |
Relationship between Learning Outcomes of Course and Program Outcomes
| # | Learning Outcomes | Program Outcomes | Method of Assessment |
|---|---|---|---|
| 1 | Learning image processing | 1͵13 | 1͵2 |
| 2 | Removing noise from images | 1͵13 | 1͵2 |
| 3 | Filtering in frequency domain | 13 | 1͵2 |
| 4 | Processing Black and White images | 1͵13 | 1͵2 |
| 5 | Ability to apply morphologic operations | 1͵13 | 1͵2 |
Work Load Details
| # | Type of Work | Quantity | Time (Hour) | Work Load |
|---|---|---|---|---|
| 1 | Course Duration | 14 | 3 | 42 |
| 2 | Course Duration Except Class (Preliminary Study, Enhancement) | 14 | 3 | 42 |
| 3 | Presentation and Seminar Preparation | 0 | 0 | 0 |
| 4 | Web Research, Library and Archival Work | 0 | 0 | 0 |
| 5 | Document/Information Listing | 0 | 0 | 0 |
| 6 | Workshop | 0 | 0 | 0 |
| 7 | Preparation for Midterm Exam | 1 | 2 | 2 |
| 8 | Midterm Exam | 1 | 2 | 2 |
| 9 | Quiz | 0 | 0 | 0 |
| 10 | Homework | 0 | 0 | 0 |
| 11 | Midterm Project | 0 | 0 | 0 |
| 12 | Midterm Exercise | 0 | 0 | 0 |
| 13 | Final Project | 0 | 0 | 0 |
| 14 | Final Exercise | 1 | 60 | 60 |
| 15 | Preparation for Final Exam | 0 | 0 | 0 |
| 16 | Final Exam | 1 | 2 | 2 |
| 150 | ||||