Machine Vision

Ivica DimitrovskiAndrea KulakovPetre Lameski

# Machine Vision

# Overview

# Contents

  • Introduction to computer vision
  • Cameras and optics
  • Brightness and color
  • Pixels and filters
  • Image processing in frequency domain
  • Image pyramid
  • Machine learning:
    • Clustering and classification
    • Edge detection and line overlapping
    • Robust line overlapping (Hough transformation, RANSAC, etc.)
    • Clustering and image segmentation
    • Gaussian Mixture Models (GMM)
    • Points of interest detection
    • Feature tracking
    • Optical flow
    • Stereo correspondence
    • Scaling- and rotation-invariant feature transformation (SIFT, SURF)
    • Visual words dictionaries
    • Recognition and classification of visual objects

# Outcomes

The goal of this course is to introduce the students to the basic concepts and principles of computer vision. The students who will successfully finish the course will be able to

  • Design efficient systems for computer vision for handwriting recognition
  • Detection and recognition of faces
  • Movement detection
  • Human and vehicle tracking
  • Gesture recognition
  • Classification and recognition of visual objects
  • Scene analysis and understanding
  • Etc.

# Methods

Lectures using presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, invited guest lecturers, independent preparation and defense of a project assignment and seminar work.

Type Effort [h]
Lectures 30
Exercises 45
Project Tasks 15
Independent Learning Tasks 15
Home Learning 75

# Materials

Author Title Publisher Year
Richard Szeliski Computer Vision: Algorithms and Applications Microsoft Research 2010
D.A. Forsyth and J. Ponce Computer Vision: A Modern Approach Prentice Hall 2002
N. Sebe, M.S. Lew Robust Computer Vision: Theory and Applications (Computational Imaging and Vision) Springer 2003

# Assessment

# Methods

Type Points/Percent
Tests 30 points
Seminar paper / Project 40 points
Activity and Learning 10 points
Final exam 20 points

# Criteria

Grade Grade (letter) Scale
5 F up to 50 points
6 E 51 to 60 points
7 D 61 to 70 points
8 C 71 to 80 points
9 B 81 to 90 points
10 A 91 to 100 points

# Requirements

# Skills

  • Basic understanding of digital image processing
  • Programming

# Equipment

  • Computer
  • Webcam

# Enrollment

Participation is free of charge. Student of partner universities can send applications to participate in courses.


# Ss. Cyril and Methodius University Skopje

Image of UKIM's University Campus

The Ss. Cyril and Methodius University in Skopje (UKIM) is the first and biggest public University in the Republic of North Macedonia, founded in 1949. At the moment, the University represents a functional community of 23 faculties, 5 research institutes, 4 public scientific institutions - associate members, 1 associate member - other higher education institutions and 7 associate members - other organizations. Its activities are stipulated by the Law on Higher Education and the Statute of the University.

Read more.

# Lecturers

Ivica Dimitrovski
Portrait of Ivica Dimitrovski

# Ivica Dimitrovski

Ivica was born in 1981 in Kratovo, Macedonia. In 2000, he started his studies with the Faculty of Electrical Engineering and Information Technologies, Saints Cyril and Methodius University of Skopje. He received the bachelor’s degree in computer science, automation and electrical engineering from the Faculty of Electrical Engineering and Information Technologies in 2005. In 2008, he received the M.Sc. degree and the Ph.D. degree in 2011.

Read more.
Andrea Kulakov
Portrait of Andrea Kulakov

# Andrea Kulakov

Andrea finished the secondary school in 1990, at age of 16, as he managed twice to take two school years during one year (7th and 8th grade in primary school and then 3rd and 4th year in high school). After that, he enrolled at the Faculty of Electrical Engineering in Skopje, Macedonia at the Computer Science Department and in 1995 graduated with the highest average grade (9.91 out of 10.00) in the generation 1990-95.

Read more.
Petre Lameski
Portrait of Petre Lameski

# Petre Lameski

Petre was born in 1985 in Kavadarci.

In 2008 he graduated at the Faculty of Electrical Engineering and Information Technologies at the University of Sts Cyril and Methodius in Skopje. In 2010 he finished his master studies at the same faculty with a thesis in the area of Robotics. From September 2008 untill September 2011 he worked as an assistant at the same faculty, teaching auditory and labaratory exercises to students in Introduction to Robotics, Distributed Computer Systems, Artificial Intelligence, Algorithms for Data Analysis, Information Systems and Mobile Information Systems.

Read more.