Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
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Mathematical analysis
2° Year It will be activated in the A.Y. 2026/2027
| Modules | Credits | TAF | SSD |
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3° Year It will be activated in the A.Y. 2027/2028
| Modules | Credits | TAF | SSD |
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One module to be chosen among the following| Modules | Credits | TAF | SSD |
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Mathematical analysis
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
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One module to be chosen among the following| Modules | Credits | TAF | SSD |
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Machine vision (2026/2027)
Teaching code
4S012388
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
I semestre dal Oct 1, 2026 al Jan 29, 2027.
Courses Single
Authorized
Learning objectives
This course aims to provide the fundamentals of image and video acquisition and processing, focusing on the physics of digital image formation, image and video processing operations, and the application of these concepts in the engineering context. The goal is to provide the student with the tools necessary to model and solve concrete problems through the processing of visual data. At the end of the course the student must demonstrate knowledge and understanding of the main image processing techniques; have the ability to apply the acquired knowledge and to interpret the results in critical way; and knowing how to develop the skills necessary to continue his/her studies autonomously in the field of visual data analysis.