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
E
-
6
A
INF/01
6
C
MAT/06
12
A
INF/01

2° Year  activated in the A.Y. 2016/2017

ModulesCreditsTAFSSD
12
B
INF/01
6
C
MAT/05
6
C
FIS/01
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
12
B
INF/01
6
B
ING-INF/05
12
B
ING-INF/05

3° Year  activated in the A.Y. 2017/2018

ModulesCreditsTAFSSD
12
B
ING-INF/05
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
6
B
INF/01
6
B
INF/01
6
B
INF/01
6
F
-
12
D
-
Prova finale
6
E
-
activated in the A.Y. 2016/2017
ModulesCreditsTAFSSD
12
B
INF/01
6
C
MAT/05
6
C
FIS/01
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
12
B
INF/01
6
B
ING-INF/05
12
B
ING-INF/05
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
12
B
ING-INF/05
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
6
B
INF/01
6
B
INF/01
6
B
INF/01
6
F
-
12
D
-
Prova finale
6
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.

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  (2017/2018)

Teaching code

4S000019

Teacher

Gloria Menegaz

Coordinator

Gloria Menegaz

Credits

6

Also offered in courses:

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Period

I sem. dal Oct 2, 2017 al Jan 31, 2018.

Lessons timetable Seminars 0

Learning outcomes

The course is meant to the acquisition of the main theoretical and practical tools that are necessary for signal and image processing. In particular the course focuses on Fourier (time/frequency) analysis, linear time-invariant systems and digital filtering. The whole pipeline from signal and image acquisition will be considered, and the main theorethical and practical aspects will be treated.
Laboratory sessions will be organized in order to "put in practice" what is treated in the course covering the entire pipeline in order to provide the student a complete view on the pipeline as well as good desing and implementation capabilities.

Program

- Introduction to image processing
- Fourier Transform (continuous time, Fourier series, discrete time, discrete Fourier transform (DFT), FFT) in one dimension
- Fourier Transform (continuous time, Fourier series, discrete time, discrete Fourier transform (DFT), FFT) in two dimensions
- The acquisition pipeline (sampling, quantization)
- Fourier Transform (Fourier series, continuous FT, discrete time FT, discrete FT, FFT, DCT)
- Signal and Image filtering (low-pass, high pass, linear and non linear)
- Image enhancement (in both spatial and frequency domain)
- Edge detection (in spatial and frequency domain)
- Region-based processing (in spatial and frequency domain)
- Morphological operators
- Color imaging
- Image segmentation (edge-based, region-based)
- Elements of pattern recognition

Examination Methods

Oral or written with evaluation of Lab sessions.

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

Teaching materials e documents