Course Name Code Semester T+U Hours Credit ECTS
Image Processing EBO 440 8 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type OPTIONAL
Course Coordinator
Course Lecturers
Course Assistants
Course Category Other
Course Objective In this course, the aim is that the students will comprehend image processing methods and will develop a computer vision system for an industrial, Security, medical etc. applications
Course Content Introduction to computer vision. To form an image matrix and neighborhood operations. Hardware and software architecture of a computer vision system. Gray level, binary and color image processing methods. Quantizing, noise reduction. Edge detection. Feature extraction. Sample applications
# Course Learning Outcomes Teaching Methods Assessment Methods
1 To inspect image acquisition systems, design systems Lecture,
2 To understand image acquisition in human vision system, learn color models and associate with vision systems Motivations to Show, Role Playing, Question-Answer, Brain Storming, Lecture, Gap Fill Tests, True False Tests,
3 To understand digital image, knowing fundamental of digital image components Lecture, Motivations to Show, Brain Storming, Role Playing, Question-Answer, Self Study, Group Study,
4 To understand image processing, inspecting basis image processing techniques Discussion, Self Study, Group Study, Sightseeing, Lecture,
5 To use image processing, writing basic image processing algorithms and inspect results Discussion, Lab / Workshop, Sightseeing, Self Study,
6 To implement image processing methods, design a system and interpret results Discussion, Sightseeing, Observation, Problem Solving,
Week Course Topics Preliminary Preparation
1 The origins of digital image processing
2 Elements of visual perception, Light and the Electromagnetic Spectrum
3 Image Sensing and Acquisition, Image Sampling and Quantization
4 Image analysis in Matlab
5 Some Basic Relationships Between Pixels
6 Image Enhancement in the Spatial Domain
7 Histogram Processing
8 Enhancement Using Arithmetic/Logic Operations
9 Basics of Spatial Filtering
10 Smoothing Spatial Filters
11 Sharpening Spatial Filters
12 Combining Spatial Enhancement Methods
13 Matlab applications
14 Matlab applications
Resources
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 To have latest knowledge and skills intended for research and practice in electronic technology X
2 To utilize equipments and instruments used in electronic technology X
3 To develop curriculum related to electronic technology and have a skill to transfer those accumulation by oral and written way X
4 To have knowledge and skills for planning, designing and managing procedures independently or in cooperation X
5 To have an open mind to ethic auditing and positive criticism, and have a constructive and interpreting attitude against scientific and social problems X
6 To disseminate and realize the environmental awareness
7 To cooperate with social organizations and the society
8 To contribute to the education of people who work under his/her responsibility and to manage some activities for their vocational careers and social rights
9 To appropriate self learning and life- long learning principles
10 To congregate in national or international scale to see individual applications on the premises and to perform some activities and mobility for professional advancement in electronic technology
# Contribution of Course Learning Outcomes to Program Outcomes PÇ 1 PÇ 2 PÇ 3 PÇ 4 PÇ 5 PÇ 6 PÇ 7 PÇ 8 PÇ 9 PÇ 10
1 To inspect image acquisition systems, design systems
2 To understand image acquisition in human vision system, learn color models and associate with vision systems
3 To understand digital image, knowing fundamental of digital image components
4 To understand image processing, inspecting basis image processing techniques
5 To use image processing, writing basic image processing algorithms and inspect results
6 To implement image processing methods, design a system and interpret results
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 65
1. Kısa Sınav 5
1. Ödev 25
2. Kısa Sınav 5
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 2 32
Mid-terms 1 10 10
Assignment 1 15 15
Performance Task (Laboratory) 1 20 20
Total Workload 125
Total Workload / 25 (Hours) 5
dersAKTSKredisi 5