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

A.A. 2024/2025 A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021 A.A. 2019/2020 A.A. 2018/2019 A.A. 2017/2018 A.A. 2016/2017 A.A. 2015/2016 A.A. 2014/2015 A.A. 2013/2014 A.A. 2012/2013 A.A. 2011/2012 A.A. 2010/2011 A.A. 2009/2010

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea in Informatica - Enrollment from 2025/2026

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

ModulesCreditsTAFSSD
6
A
MAT/02
6
A
MAT/05
12
A
ING-INF/05
6
A
FIS/01
6
A
INF/01
6
C
MAT/06
12
A
INF/01
6
E
L-LIN/12

2° Year  activated in the A.Y. 2022/2023

ModulesCreditsTAFSSD
12
B
INF/01
6
C
MAT/05
6
C
FIS/01
12
B
INF/01
6
B
ING-INF/05
6
C
ING-INF/04
12
B
ING-INF/05

3° Year  activated in the A.Y. 2023/2024

ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
INF/01
6
B
INF/01
6
B
INF/01
1 module among the following
6
C
ING-INF/06
6
C
INF/01
6
C
INF/01
6
C
ING-INF/04
6
C
INF/01
Final exam
6
E
-
activated in the A.Y. 2022/2023
ModulesCreditsTAFSSD
12
B
INF/01
6
C
MAT/05
6
C
FIS/01
12
B
INF/01
6
B
ING-INF/05
6
C
ING-INF/04
12
B
ING-INF/05
activated in the A.Y. 2023/2024
ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
INF/01
6
B
INF/01
6
B
INF/01
1 module among the following
6
C
ING-INF/06
6
C
INF/01
6
C
INF/01
6
C
ING-INF/04
6
C
INF/01
Final exam
6
E
-
Modules Credits TAF SSD
Between the years: 2°- 3°
12
D
-
Between the years: 2°- 3°
Training
6
F
-

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.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Signal and image processing (2023/2024)

Teaching code

4S000019

Credits

6

Coordinator

Marco Cristani

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Courses Single

Authorized

MoodleMoodle Seminars 0

The teaching is organized as follows:

Teoria

Credits

4

Period

Semester 1

Academic staff

Marco Cristani

Lessons timetable
Laboratorio

Credits

2

Period

Semester 1

Academic staff

Manuele Bicego

Lessons timetable

Learning objectives

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.

Prerequisites and basic notions

Mathematical analysis (series, sequences, derivatives, integrals) Probability and statistical calculations (random variables, known - Gaussian and exponential distributions)

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

Didactic methods

“The teacher / teachers will use: a) frontal lessons; b) laboratory sessions (MATLAB) c) exercises on the blackboard. Mixed mode (zoom) will NOT be present

Learning assessment procedures

Written exam, lasting 2 hours. The test consists in solving analytical exercises, in producing answers to open questions, and, as regards the laboratory part, in writing MATLAB code to solve a specific problem. It is therefore not necessary to do any separate laboratory tests. Exam methods are NOT differentiated between attending and non-attending students and for Erasmus students. The course does NOT include intermediate tests.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

Ability to identify an effective and theoretically correct technical solution to a signal and image processing problem. Ability to discursively organize knowledge; critical reasoning skills on the study carried out; quality of exposure, competence in the use of specialized vocabulary. The evaluation is expressed out of thirty.

Criteria for the composition of the final grade

26 points max for the theory part, 6 points max for the laboratory part. Honors are at the discretion of the teacher, and necessarily requires that in both modules (theory and laboratory) the maximum scores have been obtained

Exam language

italiano