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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 | 1.2 - 1.3 - 2.1 - 5.3 | 1 |  | LO - 2 :  | understand to the major applications areas of computer vision and image processing: image analysis, image restoration, image enhancement, and image compression. | 1.2 - 1.3 - 2.1 - 5.3 | 1 |  | LO - 3 :  | apply the image processing algorithms and implementation of them for different real practical applications | 1.2 - 1.3 - 2.1 - 5.3 | 1,3 |  | LO - 4 :  | have knowledge and practical skills for image and video compression (lossy and lossles) and processing. | 1.2 - 1.3 - 2.1 - 5.3 | 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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