Digital Image Processing (CMPE464) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Digital Image Processing CMPE464 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The main aim of the course is : to give an introduction to 1-D and 2-D signals, to give introduction to spatial domain and frequency domain of signals to give an introduction to theories and mathematical methods used in image analysis, to introduce the analytical tools and methods which are currently used in digital image processing, and to make the students to apply these tools in the laboratory in image restoration, enhancement and compression.
Course Learning Outcomes The students who succeeded in this course;
  • Develop theoretic and algorithmic principles behind the acquisition, display, manipulation and processing of digital images
  • Explain clearly the use of basic mathematical concepts in image analysis, in particular transform theory (in space as well as in the frequency domain), image enhancement methods, image compression and image restoration.
  • Provide development of skills to effectively integrate new concepts in image processing
Course Content Introduction to signal and image processing, introduction to digital image processing, sampling, reconstruction, and quantization, digital image representation, image transforms, enhancement, restoration, segmentation and description.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to signals and systems Other sources
2 1-D and 2-D Signals and signal processing Other source
3 Sampling and quantization of 2-D signals Other source
4 Introduction to Digital Images, and image processing applications Ch.1 (main text)
5 Fundamentals of image processing Ch.1-2 (main text)
6 Intensity Transformations and Spatial Filtering Ch. 2
7 Processing of 1-D and 2-D signals, and processing in the frequency domain, mathematical fundamentals of fast fourier transform Ch. 2
8 Image Enhancement Ch.3, Ch. 4
9 Image Restoration Ch.5
10 Color Image Processing Ch. 6
11 Image Compression Ch.8
12 Morphological Image Processing Ch.9
13 Image Segmentation Ch.10
14 Object Recognition. Ch.12

Sources

Course Book 1. Gonzalez, R. C., Woods, R. E., Digital Image Processing, Addison-Wesley, 2008.
Other Sources 2. 1. Jain, A. K., Fundamentals of digital Image Processing, Prentice-Hall.
3. 2. Castleman, K. R., Digital Image Processing, Prentice Hall.
4. 3. John G. Prokis and Dimitris G. Manolakis, “Digital Signal Processing: Principle, Algorithms and Applications” Prentice Hall Inc., Englewood Cliffs, NJ (USA), 3rd Ed., 1996.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 30
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 35
Toplam 7 100
Percentage of Semester Work 65
Percentage of Final Work 35
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Gain sufficient knowledge in mathematics, science and computing; be able to use theoretical and applied knowledge in these areas to solve engineering problems related to information systems.
2 To be able to identify, define, formulate and solve complex engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose.
3 Designs a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; applies modern design methods for this purpose.
4 To be able to develop, select and use modern techniques and tools required for the analysis and solution of complex problems encountered in information systems engineering applications; to be able to use information technologies effectively. X
5 Designs and conducts experiments, collects data, analyzes and interprets results to investigate complex engineering problems or research topics specific to the discipline of information systems engineering. X
6 Can work effectively in disciplinary and multidisciplinary teams; can work individually.
7 a. Communicates effectively both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. b. Knows at least one foreign language.
8 To be aware of the necessity of lifelong learning; to be able to access information, to be able to follow developments in science and technology and to be able to renew himself/herself continuously.
9 a. Acts in accordance with the principles of ethics, gains awareness of professional and ethical responsibility. b. Gains knowledge about the standards used in information systems engineering applications.
10 a. Gains knowledge about business life practices such as project management, risk management and change management. b. Gains awareness about entrepreneurship and innovation. c. Gains knowledge about sustainable development.
11 a. To be able to acquire knowledge about the universal and social effects of information systems engineering applications on health, environment and safety and the problems of the era reflected in the field of engineering. b. Gains awareness of the legal consequences of engineering solutions.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 1 16
Presentation/Seminar Prepration
Project
Report
Homework Assignments 5 8 40
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 129