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BIL3012 | Image Processing | 3+0+0 | ECTS:4 | Year / Semester | Spring Semester | Level of Course | First Cycle | Status | Elective | Department | DEPARTMENT of COMPUTER ENGINEERING | Prerequisites and co-requisites | None | Mode of Delivery | Face to face | Contact Hours | 14 weeks - 3 hours of lectures per week | Lecturer | Prof. Dr. Murat EKİNCİ | Co-Lecturer | None | Language of instruction | Turkish | Professional practise ( internship ) | None | | The aim of the course: | The course aims to teach basic image processing processes for computer vision deals with the processing of image data for use by a computer and to understand to the major applications areas of computer vision and image processing: image analysis, image restoration, image enhancement, and image compression |
Learning Outcomes | CTPO | TOA | Upon successful completion of the course, the students will be able to : | | | LO - 1 : | learn basic image processing processes for computer vision deals with the processing of image data for use by a computer | 2,3,4,12 | 1 | LO - 2 : | understand to the major applications areas of computer vision and image processing: image analysis, image restoration, image enhancement, and image compression. | 2,3,4,12 | 1 | LO - 3 : | apply the image processing algorithms and implementation of them for different real practical applications | 2,3,4,12 | 1,3 | LO - 4 : | have knowledge and practical skills for image and video compression (lossy and lossles) and processing. | 2,3,4,12 | 1,3 | 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 | |
Elements of Digital Image Processing systems, Image Formating and Sensing; Imaging geometry; Image Analysis, Preprocessing, spatial filters; First-Second order based edge detection and their applications; Image Segmentation; Thresholding-Edge-Region Based segmentation; Discrete transforms in image processing (Fourier, Cosine, Walsh-Hadamard, Wavelet transforms) and its applications; Model based object detection via Hough transform; Mathematical morphology; Feature Extraction and Analysis; Pattern Classification and recognition; Image enhancement; Image restoration, and geometric transforms; Image compression with lossles compression methods; Lossy compression methods, and fundamentals of the common compression methods: JPEG, MPEG, H.363. |
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Course Syllabus | Week | Subject | Related Notes / Files | Week 1 | Elements of Digital Image Processing systems, Image Formating and Sensing. | | Week 2 | Imaging geometry, | | Week 3 | Image Analysis, Preprocessing, spatial filters | | Week 4 | First-Second order based edge detection and their applications | | Week 5 | Image Segmentation; Thresholding-Edge-Region Based segmentation | | Week 6 | Discrete transforms in image processing (Fourier, Cosine, Walsh-Hadamard, Wavelet transforms) and its applications | | Week 7 | Model based object detection via Hough transform, | | Week 8 | Mathematical morphology, | | Week 9 | Mid-term exam | | Week 10 | Feature Extraction and Analysis | | Week 11 | Pattern Classification and recognition, | | Week 12 | Image enhancement, | | Week 13 | Image restoration, and geometric transforms | | Week 14 | Image compression with lossles compression methods, | | Week 15 | Lossy compression methods, and fundamentals of the common compression methods: JPEG, MPEG, H.363 | | Week 16 | End-of-term exam | | |
1 | Scott E. Umbaugh, 2005; Computer Imaging: Digital Image Analysis and Processing, A CRC Press Book, Taylor and Francis Group | | |
1 | Rafael C. Gonzales, Richard E. Woods. 1998; Digital Image Processing, Addison-Wesley Publishing Company | | 2 | Milan Sonka, Vaclav Hlavac, Roger Boyle. 1999; Image Processing, Analysis, and Machine Vision, Second Edition, PWS Puıblishing, | | |
Method of Assessment | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | Mid-term exam | 9 | 08/04/2013 | 2 | 30 | Project | 15 | 13/05/2013 | 2 | 20 | End-of-term exam | 16 | 02/06/2013 | 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 | 4 | 12 | Sınıf dışı çalışma | 2 | 14 | 28 | Arasınav için hazırlık | 10 | 1 | 10 | Arasınav | 2 | 1 | 2 | Proje | 3 | 12 | 36 | Dönem sonu sınavı için hazırlık | 12 | 1 | 12 | Dönem sonu sınavı | 2 | 1 | 2 | Total work load | | | 102 |
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