GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
FUZZY LOGIC BASED IMAGE PROCESSING/5031333
Course Title: FUZZY LOGIC BASED IMAGE PROCESSING
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
General information about fuzzy logic and image processing.
Fuzzy color space.
Color similarity
Image segmentation. Fuzzy logic based image segmentation.
Fuzzy logic based image filter.
 -- MODE OF DELIVERY
  Face to face course, writing codes and applications
 --WEEKLY SCHEDULE
1. Week  General information about fuzzy logic and image processing
2. Week  Fuzzy color space
3. Week  Color similarity
4. Week  Rule-based gradient calculation
5. Week  Edge detection
6. Week  Threshold selection methods
7. Week  Image segmentation methods
8. Week  Midterm exam, K-means algorithm
9. Week  Fuzzy C-means algorithm
10. Week  Rule-based segmentation
11. Week  Rule-based segmentation
12. Week  Rule-based filter design
13. Week  Nonlinear filters:diffusion filter
14. Week  Rule-based diffusion filter design
15. Week  
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
2
20
 Application
0
0
 Projects
1
20
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
14
3
42
 Searching in Internet and Library
14
2
28
 Material Design and Implementation
10
2
20
 Report Preparing
2
10
20
 Preparing a Presentation
0
0
0
 Presentation
0
0
0
 Midterm Exam and Preperation for Midterm Exam
2
10
20
 Final Exam and Preperation for Final Exam
2
10
20
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
192
 TOTAL WORKLOAD / 25: 
7.68
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Putting into practice and/or developing scientific methods by deepening and improving information acquired at a former level.X
2The ability to solve complex problems independently by developing analysis, synthesis, critical thinking and problem solving capabilities and/or to find original solutions to addressed problems.X
3Designing a process or a system by using modern design methods and tools.X
4To be able to collect, evaluate and interpret data by means of scientific methods and access to new information systematically by using appropriate scientific methods.X
5Gaining the ability to determine solution methods and/or to develop scientific methods by taking part in multidisciplinary teams and integrating information from different areas within study field.X
6The ability to determine the appropriate tools in the processes of scientific research and to use information technologies effectively.X
7The ability to plan and manage projects, to define alternative solutions and/or to develop alternative solution methods to defined problems.X
8The ability to present his/her accumulation of scientific knowledge oral and in written.X
9The ability to contribute into science by publishing novel scientific results in national /international journals.X
10The ability to defend his/her thesis or scientific methods in front of expert groups.X
11The ability to update his/her knowledge continuously by following the scientific developments.X
12The ability to take into account the social, environmental and ethical values while conducting a scientific research and/or to produce solutions in social, environmental and ethical subjects.X
 -- NAME OF LECTURER(S)
   (Prof. Dr. Recep Demirci)
 -- WEB SITE(S) OF LECTURER(S)
   (http://websitem.gazi.edu.tr/site/rdemirci)
 -- EMAIL(S) OF LECTURER(S)
   (rdemirci@gazi.edu.tr)