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.
Type D and Type F activities
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite.
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 3° | Control theory | D |
Riccardo Muradore
(Coordinator)
|
| 3° | Biomedical Data and Signal Processing | D |
Silvia Francesca Storti
(Coordinator)
|
| 3° | Matlab-Simulink programming | D |
Bogdan Mihai Maris
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 3° | Introduction to 3D printing | D |
Franco Fummi
(Coordinator)
|
| 3° | Python programming language | D |
Vittoria Cozza
(Coordinator)
|
| 3° | HW components design on FPGA | D |
Franco Fummi
(Coordinator)
|
| 3° | Rapid prototyping on Arduino | D |
Franco Fummi
(Coordinator)
|
| 3° | Protection of intangible assets (SW and invention)between industrial law and copyright | D |
Roberto Giacobazzi
(Coordinator)
|
| years | Modules | TAF | Teacher | |
|---|---|---|---|---|
| 1° | Subject requirements: mathematics | D |
Rossana Capuani
|
|
| 3° | The fashion lab (1 ECTS) | D |
Maria Caterina Baruffi
(Coordinator)
|
|
| 3° | LaTeX Language | D |
Enrico Gregorio
(Coordinator)
|
|
Signal and image processing (2020/2021)
Teaching code
4S000019
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Teoria
Laboratorio [II turno]
Laboratorio [I turno]
Learning outcomes
The aim of this course is to provide the basic knowledge of methods and models for biomedical signal and image processing, developing the ability to analyze and solve problems of interest, mainly in the biomedical field. Each technique presented will be accompanied by applications on simulated and real signals.
At the end of the course, the student will be able to show knowledge of the main methods of biomedical signals and image processing. They will possess the ability to formulate, ana- lyze and solve problems of interest in bioengineering, through the acquired theoretical and practical basic knowledge. Finally, the student will be able to evaluate the traditional methods in the biomedical sciences in order to devise new approaches to methodological problems with clinical reversibility.
Program
- Introduction to the signal and image processing
- Preliminary mathematics
- Signals and their taxonomy
- Fourier analysis, 1D and 2D
- Methods for improving image quality (image enhancement) in both the spatial and frequency domains
- Extraction of image contours
- Extraction of image regions
- Morphological operators
- Representation and processing of color images
Examination Methods
Written with evaluation of Lab sessions.
