Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
7EEE 445INTRODUCTION TO COMPUTER VISION4+0+04501.04.2026

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program ELECTRICAL-ELECTRONICS E.
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course To introduce students to Computer Vision, an area of increasing importance in the technologies of robotics and human-computer interaction. Also this course will give an understanding of some of the central issues in computer vision, including its relationship to some aspects of biological vision, and to develop the skills needed to write simple applied computer vision programs using a suitable programming language.
Course Content History of computer vision, Illumination, sensors and cameras. Image acquisition and representation. Fundemental of digital image processing. Linear filters, edge detection, segmentation. Representation and description.Object recognition.

Illumination, sensors and cameras. Image acquisition and representation. Fundemental of digital image processing. Linear filters, edge detection, segmentation. Representation and description.Object recognition.


history of computer vision, Illumination, sensors and cameras. Image acquisition and representation. Fundemental of digital image processing. Linear filters, edge detection, segmentation. Representation and description.Object recognition
Course Methods and Techniques 1 - Lecture, 2 - Question - Answer, 3 - Discussion, 4 - Drill and Practice, 14 - Self Study
Prerequisites and co-requisities ( EEE 301 )
Course Coordinator None
Name of Lecturers Prof.Dr. SEMA KAYHAN skoc@gantep.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Computer Vision. A modern Approach. Forsyth and Ponce
Digital Image Processing, R.C. Gonzalez, R.E. Woods.
Course Notes Forsyth Ponce Computer Vision: A Modern Approach 2003. Prentice-Hall
Gonzalez Woods Digital Image Processing Prentice hall

Course Category
Mathematics and Basic Sciences %20
Engineering %60
Engineering Design %20

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 2 % 60
Practice 1 % 0
Final examination 1 % 40
Total
4
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 4 56
Hours for off-the-c.r.stud 14 4 56
Mid-terms 2 10 20
Practice 1 10 10
Final examination 1 10 10
Total Work Load   Number of ECTS Credits 5 152

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 analyze visual data to recognize and understand the world captured by cameras as images or video sequences.
2 The basic concepts of image processing are learned.
3 Students learn fundamental aspects of image processing, including hardware, software, digitization, enhancement, encoding, segmentation, and feature recognition.
4 image processing algorithms can be analyzed and programmed.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to computer vision, introduction and brief history. book Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
2 Imaging Geometry, Camera Modeling, Pinhole Cameras, Projections (Perspective, Weak Perspective and Orthographic) . Lenses and their effect. book Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
3 Digital image fundamentals; image acquisition, sampling, quantization, image enhancement, image formats book Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
4 Binary image analysis; pixels and neighborhoods, mathematical morphology, connected component analysis, automatic thresholding. book Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
5 Linear filtering; spatial domain filter. book Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
6 Frquencydomain filtering. book Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
7 MIDTERM EXAM I BOOKS, LECTURE NOTES Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
8 Image Restoration Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
9 Edge detection; edges, lines, arcs, Hough transform. BOOK Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
10 Image Segmentation; histogram based approaches BOOK Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
11 Region Segmentation and Description; Region growing, Split-and-merging. BOOK Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
12 MIDTERM EXAM 2 BOOK Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
13 Morphological Image Processing; Graph-based approaches. BOOK Forsyth Ponce Computer Vision: A Modern Approach 2003. Gonzalez Woods Digital Image Processing
14 Review gözden geçirmek

 
Sustainable Development Goals
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
All 3 3 3 4 4
C1 3 4
C2 4 4 2 4 4
C3 5 5
C4 5 5 2 5 5

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  https://obs.gantep.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=337792&lang=en