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| ELK4009 | Image Processing | 2+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of ELECTRICAL and ELECTRONICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Prof. Dr. Ali GANGAL | | Co-Lecturer | Prof. Dr. Temel KAYIKÇIOĞLU | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The objective of this course is to give the student fundamental knowledge of the major topics of digital image processing: representation, processing techniques, and communication. Students will confirmate of their theoretical knowledge by computer simulations using MATLAB. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | understand image acquisition and image definition | 1,3,5 | 1 | | LO - 2 : | do image enhancement in spatial domain and frequency domain | 1,3,5 | 1 | | LO - 3 : | do color image processing applications | 1,3,5 | 1 | | LO - 4 : | do image and video compression | 1,3,5,15 | 1 | | LO - 5 : | design image communications systems | 1,3,5,15 | 1 | | LO - 6 : | preform examples from all topics in Matlab environment | 1,3,5,15 | 1 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Introduction. Digital Image Fundamentals. Image Enhancement in the Spatial Domain. Image Enhancement in the Frequency Domain. Image Restoration. Color Image Processing. Image Compression. Image communications systems. Image processing applications using MATLAB. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction. Digital image fundamentals. | | | Week 2 | Image enhancement. | | | Week 3 | Image enhancement. | | | Week 4 | Image restoration. | | | Week 5 | Image restoration. | | | Week 6 | Image restoration. | | | Week 7 | Image restoration. | | | Week 8 | Color image processing. | | | Week 9 | Mid-term exam | | | Week 10 | Color image processing. | | | Week 11 | Color image processing. | | | Week 12 | Image compression. | | | Week 13 | Image compression. | | | Week 14 | Image segmentation. | | | Week 15 | Image segmentation. | | | Week 16 | End-of-term exam | | | |
| 1 | Gonzalez, G. C., Woods, R. E., "Digital Image Processing", Prentice Hall, 2002. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 18/11/2013 | 2 | 30 | | Homework/Assignment/Term-paper | 14 | 23/12/2013 | 10 | 20 | | End-of-term exam | 16 | 08/01/2014 | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 4 | 14 | 56 | | Arasınav için hazırlık | 5 | 1 | 5 | | Arasınav | 2 | 1 | 2 | | Ödev | 10 | 1 | 10 | | Dönem sonu sınavı için hazırlık | 5 | 1 | 5 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 122 |
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