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.

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I sem. Oct 2, 2017 Jan 31, 2018
II sem. Mar 1, 2018 Jun 15, 2018
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2018 Feb 28, 2018
Sessione estiva d'esame Jun 18, 2018 Jul 31, 2018
Sessione autunnale d'esame Sep 3, 2018 Sep 28, 2018
Degree sessions
Session From To
Sessione di laurea estiva Jul 18, 2018 Jul 18, 2018
Sessione di laurea autunnale Nov 22, 2018 Nov 22, 2018
Sessione di laurea invernale Mar 20, 2019 Mar 20, 2019
Holidays
Period From To
Christmas break Dec 22, 2017 Jan 7, 2018
Easter break Mar 30, 2018 Apr 3, 2018
Patron Saint Day May 21, 2018 May 21, 2018
Vacanze estive Aug 6, 2018 Aug 19, 2018

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

B C D F G M O P Q R S T V Z

Ballottari Matteo

matteo.ballottari@univr.it 045 802 7098

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Bonnici Vincenzo

vincenzo.bonnici@univr.it +39 045 802 7045

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

andrea.calanca@univr.it +39 045 802 7847

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Capaldi Stefano

stefano.capaldi@univr.it +39 045 802 7907

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Dall'Alba Diego

diego.dallalba@univr.it +39 045 802 7074

Della Libera Chiara

chiara.dellalibera@univr.it +39 0458027219

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Dell'Orco Daniele

daniele.dellorco@univr.it +39 045 802 7637

Dominici Paola

paola.dominici@univr.it 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

mariapina.donofrio@univr.it 045 802 7801

Drago Nicola

nicola.drago@univr.it 045 802 7081

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Giorgetti Alejandro

alejandro.giorgetti@univr.it 045 802 7982

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Maris Bogdan Mihai

bogdan.maris@univr.it +39 045 802 7074

Menegaz Gloria

gloria.menegaz@univr.it +39 045 802 7024

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Paci Federica Maria Francesca

federicamariafrancesca.paci@univr.it +39 045 802 7909

Piccinelli Fabio

fabio.piccinelli@univr.it +39 045 802 7097

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Romeo Alessandro

alessandro.romeo@univr.it +39 045 802 7974-7936; Lab: +39 045 802 7808

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Storti Silvia Francesca

silviafrancesca.storti@univr.it +39 045 802 7908

Trabetti Elisabetta

elisabetta.trabetti@univr.it 045/8027209

Valenti Maria Teresa

mariateresa.valenti@univr.it +39 045 812 8450

Villa Tiziano

tiziano.villa@univr.it +39 045 802 7034

Zivcovich Franco

franco.zivcovich@univr.it

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 enrolment year.

ModulesCreditsTAFSSD
One course to be chosen among the following
Other activitites
3
F
-
Final exam
3
E
-

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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S003710

Credits

12

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

The teaching is organized as follows:

Segnali teoria

Credits

4

Period

I semestre

Academic staff

Gloria Menegaz

Immagini teoria

Credits

4

Period

I semestre

Academic staff

Alessandro Daducci

Segnali laboratorio

Credits

2

Period

I semestre

Academic staff

Gloria Menegaz

Immagini laboratorio

Credits

2

Period

I semestre

Academic staff

Alessandro Daducci

Learning outcomes

The purpose of the course is to introduce the main theoretical and practical tools that are necessary for signal and image processing, including both natural and medical images.
At the end of the course, the students will be able to apply the methodologies studied and employ image processing software tools for tackling some typical tasks in the analysis of medical and biomedical images.

Program

------------------------
Part 1: Signal processing - Theory
------------------------
- Introduction to signal and image processing - Fourier transform in one dimension - A/D conversion (sampling, quantization) - Digital filtering (low-pass, high-pass, linear, non-linear) - Fourier transform in two dimensions - Image enhancement - Bases of image segmentation (edge-based, region-based) - Applications
------------------------
Part 1: Signal processing - Lab
------------------------
The Lab activity will consist in solving exercises in Matlab concerning the topics covered during the lessons.

------------------------
Part 2: Image processing - Theory
------------------------
- Recall of basic notions on segnals (time and frequency domain, Fourier transform...) - Digital image fundamentals - Histogram and point operations - Spatial filtering (spatial and frequency domain) - Restoration - Feature extraction (points, lines, edges) - Morphological operations - Geometric transformations and registration - Segmentation - Compression
------------------------
Part 2: Image processing - Lab
The hands-on part starts with a guided-session to practice with the topics covered during the course by using functions/procedures already implemented inn MATLAB. During the remaining of the session students will have time to implement themselves some algorithms seen during the course.

Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Segnali teoria Rafael C. Gonzalez and Richard E. Woods Digital Image Processing (Edizione 4) Prentice Hall College Div 2017 0133356728
Segnali teoria B.P. Lathi Signal Processing and Linear Systems Berkeley-Cambridge 1998 0-941413-35-7
Immagini teoria Rafael C. Gonzalez and Richard E. Woods Digital Image Processing (Edizione 4) Prentice Hall College Div 2017 0133356728
Immagini laboratorio Stormy Attaway Matlab: A Practical Introduction to Programming and Problem Solving (Edizione 3) Elsevier 2013 978-0-12-405876-7

Examination Methods

The grade for Part 1 (Signal processing) will be the mean of the grades of the theory and lab exams rounded to the nearest integer.
------------------------
Part 1: Signal processing - Theory
------------------------
Written exam on the topics covered during the course.

------------------------
Part 1: Signal processing - Lab
------------------------
The Lab. activity will be verified by a final exam consisting in the solution of exercises in Matlab similar to those solved during the course Lab sessions.

------------------------
Part 2: Image processing - Theory
------------------------
The aim of the written exam consists in verifying the comprehension of course contents and the capability to apply these contents for generalizing case studies presented during the course and for facing new issues. The written exams includes both open questions about the theory as well as exercises.
------------------------
Part 2: Image processing - Lab
------------------------
The aim of the laboratory exam is to verify the acquisition of the tools and methods and to assess the ability to apply such knowledge to the solution of new problems. The exam consists of an implementation part, where students have to implement themselves some of the algorithms seen during the course, as well as of solving some exercises using built-in MATLAB functions.

The final grade will be the mean of the grades of the two modules, rounded to the nearest integer.

Type D and Type F activities

Modules not yet included

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.


Graduation

List of theses and work experience proposals

Stage Research area
Correlated mutations Various topics

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management


Area riservata studenti