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Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
COMPUTER VISION BSM 466 8 3 + 0 3 5
Ön Koşul Dersleri
Önerilen Seçmeli Dersler
Dersin Dili Türkçe
Dersin Seviyesi Lisans
Dersin Türü SECMELI
Dersin Koordinatörü Dr.Öğr.Üyesi SERAP KAZAN
Dersi Verenler
Dersin Yardımcıları
Dersin Kategorisi
Dersin Amacı
It is generally necesary to use a computer vision system in an industrial automation system. Especially, part counting, quality control and other applications like these are generally done by computer vision.

In this course, the aim is make students learn image processing methods, and develop a computer vision system for an industrial application.
Dersin İçeriği
Introduction to computer vision. To form an image matrix and neighbourhood 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. Fundamentals of 3-D image processing. Sample applications
Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri
1 - Understand computer vision hardware and software elements 1 - 14 - A - C - D -
2 - Understand computer vision systems 1 - 4 - 14 - 16 - A - C - D -
3 - Constitute image processing algorithms and code them 1 - 4 - 15 - 16 - A - C - D -
4 - Design an industrial image processing system. 14 - 15 - 16 - C - D -
Öğretim Yöntemleri: 1:Lecture 14:Self Study 4:Drilland Practice 16:Project Based Learning 15:Problem Solving
Ölçme Yöntemleri: A:Testing C:Homework D:Project / Design

Ders Akışı

Hafta Konular ÖnHazırlık
1 Introduction to computer vision
2 Hardware and sofware architecture of a computer vision system
3 Forming an image matrix and neighbourhood operations.
4 Gray level, binary and color image processing and their usage area.
5 Quantizing, Threshold, histogram and noise reduction techinques.
6 Edge detection and corner detection
7 Image analysis towards pattern recognition
8 Pixel based operations on images.
9 Feature extraction for computer vision based classification applications.
10 Image processing in automatic visual inspection and quality control systems
11 Fundamentals of 3-D Image processing
12 Industrial computer vision applications and presentations by students.
13 Sample applications and presentations by students.
14 Sample applications and presentations by students.

Kaynaklar

Ders Notu Lecture Notes
Ders Kaynakları 1. GONZALEZ R.C., WOODS R.E., and ADDINS S.L., Digital Image Processing Using Matlab, Pearson Education Inc., New Jersey, 2004.
2. LOW A., Introductory Computer Vision and Image Processing, McGrow-Hill, 1991, ENGLAND.
3. AWCOCK G.J. and THOMAS R., Applied Image Processing, McGrow-Hill, Inc., 1996.
4. JAHNE B., Digital Image Processing, Springer-Verlag, 2005, Netherlands.
5. DAVIES, E.R., Machine vision: Theory, Algorithms, Practicalities, Academic Pres, 1997.
6.. UMBAUGH S. E., Computer Vision and Image Processing, Prentice-Hall, 1998, USA.

Döküman Paylaşımı


Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
1 2 3 4 5
1 To have sufficient foundations on engineering subjects such as science and discrete mathematics, probability/statistics; an ability to use theoretical and applied knowledge of these subjects together for engineering solutions, X
2 An ability to determine, describe, formulate and solve engineering problems; for this purpose, an ability to select and apply proper analytic and modeling methods,al background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations X
3 An ability to select and use modern techniques and tools for engineering applications; an ability to use information technologies efficiently, X
4 An ability to analyze a system, a component or a process and design a system under real limits to meet desired needs; in this direction, an ability to apply modern design methods, X
5 An ability to design, conduct experiment, collect data, analyze and comment on the results and consciousness of becoming a volunteer on research,
6 Understanding, awareness of administration, control, development and security/reliability issues about information technologies,
7 An ability to work efficiently in multidisciplinary teams, self confidence to take responsibility, X
8 An ability to present himself/herself or a problem with oral/written techniques and have efficient communication skills; know at least one extra language, X
9 An awareness about importance of lifelong learning; an ability to update his/her knowledge continuously by means of following advances in science and technology, X
10 Understanding, practicing of professional and ethical responsibilities, an ability to disseminate this responsibility on society,
11 An understanding of project management, workplace applications, health issues of laborers, environment and job safety; an awareness about legal consequences of engineering applications, X
12 An understanding universal and local effects of engineering solutions; awareness of entrepreneurial and innovation and to have knowledge about contemporary problems.

Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 65
KisaSinav 1 5
KisaSinav 2 5
Odev 1 25
Toplam 100
Yıliçinin Başarıya Oranı 50
Finalin Başarıya Oranı 50
Toplam 100

AKTS - İş Yükü

Etkinlik Sayısı Süresi(Saat) Toplam İş yükü(Saat)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 10 10
Quiz 2 4 8
Assignment 1 8 8
Final examination 1 15 15
Toplam İş Yükü 137
Toplam İş Yükü /25(s) 5.48
Dersin AKTS Kredisi 5.48
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