BMM038 Applied Digital Image Processing

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code BMM038
Name Applied Digital Image Processing
Term 2022-2023 Academic Year
Term Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Doç. Dr. AHMET AYDIN
Course Instructor
1


Course Goal / Objective

Teaching the students fundamentals of digital image processing and applying those methods on sample images.

Course Content

Fundamentals of Digital Images, Conerting Between Classes, Intensity Transformation Functions, Histogram Processing, Spatial Filtering, 2D Fourier Transform, Flterinf in the Frequency Domain, Noise Models, Image Reconstruction, Geometric Transformations, Color Image Processing, Morphological Image Processing, Image Segmentation

Course Precondition

None

Resources

Gonzalez, R. C., Woods, R. E., Eddins, S. L., & Woods, R. E. (Richard E. (2004). Digital Image processing using MATLAB

Notes

Lecture notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Students learn digital image processing techniques and can use them
LO02 Students learn and apply digital image filtering both in spatal and frequency domains
LO03 Studenst learn and apply gometric traansformations.
LO04 Students learn and apply image segmentation.
LO05 Students learn and apply morphological image processing.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal To be able to solve scientific problems encountered in the field of medicine and medical technologies by applying current and advanced technical approaches of mathematics, science and engineering sciences. 5
PLO02 Yetkinlikler - Öğrenme Yetkinliği To have a knowledge of the literature related to a sub-discipline of biomedical engineering, to define and model current problems. 4
PLO03 Beceriler - Bilişsel, Uygulamalı Ability to analyze data, design and conduct experiments, and interpret results 4
PLO04 Beceriler - Bilişsel, Uygulamalı Developing researched contemporary techniques and computational tools for engineering applications 5
PLO05 Beceriler - Bilişsel, Uygulamalı To be able to analyze and design a process in line with a defined target 5
PLO06 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Conducting scientific studies with a medical doctor from an engineering perspective. 4
PLO07 Yetkinlikler - İletişim ve Sosyal Yetkinlik Expressing own findings orally and in writing, clearly and concisely.
PLO08 Yetkinlikler - Öğrenme Yetkinliği To be able to improve oneself by embracing the importance of lifelong learning and by following the developments in science-technology and contemporary issues.
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Ability to act independently, set priorities and creativity.
PLO10 Yetkinlikler - Alana Özgü Yetkinlik Being aware of national and international contemporary scientific and social problems in the field of Biomedical Engineering.
PLO11 Yetkinlikler - Alana Özgü Yetkinlik To be able to evaluate the contribution of engineering solutions to problems in medicine, medical technologies and health in a global and social context.


Week Plan

Week Topic Preparation Methods
1 Introduction Reading Chapter 1 Öğretim Yöntemleri:
Anlatım
2 Digital Image Representation, Reading and Writing Images, Image Types Reading Chapter 2 Öğretim Yöntemleri:
Anlatım
3 Intensity Transformation, Histogram Processing Section 3.1, 3.2, 3.3 Öğretim Yöntemleri:
Anlatım
4 Spatial Filtering Section 3.4 Öğretim Yöntemleri:
Anlatım
5 2D Discrete Fourier Transform, Frequency Domain Filterin - I Section 4.1, 4.2, 4.3 Öğretim Yöntemleri:
Anlatım
6 Frequency Domain Filterin - II Section 4.4, 4.5, 4.6 Öğretim Yöntemleri:
Anlatım
7 Noise Models, Image Reconstruction, Image Reconstruction from Projections Section 5.1, 5.2, 5.11 Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Lecture Notes Ölçme Yöntemleri:
Yazılı Sınav
9 Geometric Transformations Section 6.1, 6.2, 6.3 Öğretim Yöntemleri:
Anlatım
10 Color Image Processing Chapter 7 Öğretim Yöntemleri:
Anlatım
11 Morphological Image Processing Chapter 10 Öğretim Yöntemleri:
Anlatım
12 Image Segmentation I Section 11.1, 11.2,11.3 Öğretim Yöntemleri:
Anlatım
13 Image Segmentation II Section 11.4, 11.5 Öğretim Yöntemleri:
Anlatım
14 Semester Project - I Example Projescts Öğretim Yöntemleri:
Anlatım
15 Semester Project - II Example Projescts Öğretim Yöntemleri:
Anlatım
16 Term Exams Lecture Notes Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Lecture Notes Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 16.11.2022 01:41