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FACULTY of SCIENCE / DEPARTMENT of STATISTICS and COMPUTER SCIENCES /
Katalog Ana Sayfa
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IST3022Digital Image Processing4+0+0ECTS:6
Year / SemesterSpring Semester
Level of CourseFirst Cycle
Status Elective
DepartmentDEPARTMENT of STATISTICS and COMPUTER SCIENCES
Prerequisites and co-requisitesNone
Mode of DeliveryFace to face, Group study
Contact Hours14 weeks - 4 hours of lectures per week
LecturerDoç. Dr. Orhan KESEMEN
Co-LecturerDOCTOR LECTURER Uğur ŞEVİK
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
To learn image processing techniques using mathematics, statistics and computer science. Package program development skills to win.
 
Learning OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
LO - 1 : To easier understand Image processing programs.2,3,4,5,6,7,111,3
LO - 2 : To learn Image processing techniques.1,4,10,111,3
LO - 3 : To learn use of mathematics, andstatistics such as the theoretical sciences applications in the areas.2,4,5,7,8,9,10,111,3
LO - 4 : Package to learn how to program development.7,91,3
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

 
Contents of the Course
Introduction to image processing; use of components of color, color space, digitizing and quantization. Point Processes: arithmetic, logical, look up table, histogram equalization, contrast stretching, auto contrast and finally contrast, intensity transformation. Area Processes: convolution and correlation; blur; sharp; median, mode, max, min and other descriptive statistical methods on area process. Geometric Process: inverse mapping, interpolation, scaling, rotating, mirror and translation; Frame Process: arithmetic, bitwise. Integral Transform: one and two dimensional Fourier transform, amplitude, frequency, discrete Fourier transform and fast Fourier; Cosine and Hilbert transform; Walsh and Hadamard transform.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Introduction to image processing, digitization and quantisation process;
 Week 2Introduction to Csharp
 Week 3Image Processing Using Csharp
 Week 4The use of color components, color spaces,
 Week 5Point process: arithmetic and binary operations, histogram equalization and matching,
 Week 6Point processes II: the density transformation, contrast improvement;
 Week 7Area Processes I: convolution and relationship concepts,
 Week 8Area Processes II: median, mode, and other statistical filters;
 Week 9Mid-term exam
 Week 10Geometric transformations: interpolation scaling, rotation, transation, crop, miror;
 Week 11Morphologic transformation: variable scaling, rotation and transation,
 Week 12Frame operations, arithmetic, quadratic, complex, binary and proportional operations;
 Week 13Integral transformations I: Cosine transform.
 Week 14Integral transformations II: Fourier transform.
 Week 15Integral transformations III: Walsh and Hadamard transform.
 Week 16End-of-term exam
 
Textbook / Material
1Orhan KESEMEN, C# ile Görüntü İşlemeye Giriş, (Baskıda)
 
Recommended Reading
1Rafael C. Gonzalez and Richard E. Woods, 1992; Digital Image Processing, Addision-Wesley, New York
2Tinku Acharya and Ajoy K. Ray, 2005; Image Processing : Principles and Applications, Wiley,
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 12/04/2019 1 50
End-of-term exam 16 31/05/2019 1 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 4 14 56
Sınıf dışı çalışma 3 14 42
Ödev 3 10 30
Kısa sınav 1 1 1
Dönem sonu sınavı için hazırlık 6 1 6
Dönem sonu sınavı 1 1 1
Total work load136