|
YZM3032 | Image Processing | 2+0+0 | ECTS:4 | Year / Semester | Spring Semester | Level of Course | First Cycle | Status | Elective | Department | DEPARTMENT of SOFTWARE ENGINEERING | Prerequisites and co-requisites | None | Mode of Delivery | Face to face, Practical | Contact Hours | 14 weeks - 2 hours of lectures per week | Lecturer | Dr. Öğr. Üyesi Asuman GÜNAY YILMAZ | Co-Lecturer | | Language of instruction | Turkish | Professional practise ( internship ) | None | | The aim of the course: | The aim of the course is to teach the students basic image processing methods and algorithms in spatial and frequency domains, to solve the image processing problems they encounter in real life, to gain the ability to develop applications for image enhancement, compression, segmentation and recognition. |
Learning Outcomes | CTPO | TOA | Upon successful completion of the course, the students will be able to : | | | LO - 1 : | Know basic concepts and approaches related to image processing | 1,3,8,12 | | LO - 2 : | Know image color spaces, image formats, image compression algorithms | 1,3,8,12 | | LO - 3 : | Apply image filtering, enhancement, segmentation algorithms | 1,3,8,12 | | LO - 4 : | Learn morphological image processing algorithms. | 1,3,8,12 | | LO - 5 : | Understands the methods of extracting features from images. | 1,3,8,12 | | LO - 6 : | Gain the ability to develop image processing applications to solve a specific problem | 1,3,8,12 | | 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 | |
Digitization of the analog signal, sampling, quantification, Creation of 2D images, resolution, bit-depth, concepts, convolution, Color spaces and image storage / compression formats, Image filtering, blurring, edge detection, sharpening, Methods of image enhancement, histogram equalization / matching, Image segmentation, Frequency domain image processing, FFT, DCT transformations, Morphological image processing, Feature extraction, Image morphing, Image processing applications |
|
Course Syllabus | Week | Subject | Related Notes / Files | Week 1 | Digitization of the analog signal, sampling, quantification | | Week 2 | Creation of 2D images, resolution, bit-depth, concepts, convolution | | Week 3 | Color spaces and image storage / compression formats, | | Week 4 | Image filtering, blurring, edge detection, sharpening | | Week 5 | Methods of image enhancement, histogram equalization / matching | | Week 6 | Image segmentation | | Week 7 | Frequency domain image processing | | Week 8 | FFT, DCT transformations | | Week 9 | Midterm exam | | Week 10 | Morphological image processing | | Week 11 | Feature extraction from images | | Week 12 | Feature extraction from images | | Week 13 | Image morphing | | Week 14 | Image processing applications | | Week 15 | Image processing applications | | Week 16 | Final exam | | |
1 | Rafael C. Gonzales, Richard E. Woods. 1998; Digital Image Processing, Addison-Wesley Publishing Company | | |
Method of Assessment | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | Mid-term exam | 9 | | 2 | 50 | End-of-term exam | 16 | | 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 | 2 | 14 | 28 | Sınıf dışı çalışma | 3 | 14 | 42 | Arasınav için hazırlık | 4 | 5 | 20 | Arasınav | 2 | 1 | 2 | Dönem sonu sınavı için hazırlık | 4 | 5 | 20 | Dönem sonu sınavı | 2 | 1 | 2 | Total work load | | | 114 |
|