Course description

Description: The aim of the course is to give an intorduction to the basic algorithms used in digital image processing and computer vision.


Prerequisits: Good programming background, data structures, linear algebra, vector calculus, basics of signal processing. No prior knowledge of image processing or computer vision is assumed.

Classes per week: 2 lessons lecture (seminar) + 2 lessons laboratory excercise each week

Total credit points: 5

Type of the exam: oral assessment


Lecturer and course responsible:

Csaba Benedek, PhD, associate professor, e-mail:


Excercise leaders and instructors:

• Miklós Koller, PhD, assistant professor (e-mail: koller.miklos at

• Balazs Nagy, PhD student (e-mail: at

• Márton Bese Naszlady (e-mail: naszlady.marton.bese at

• Ágnes Szabó (e-mail: szabo.agnes at

• Péter Bogdány (e-mail: bogdany.peter at

• Bendegúz T. Módli (e-mail: modli.tamas.bendeguz at