(click to insert) - SEGNALI E IMMAGINI I (2020/2021)

Course code
Academic sector
Language of instruction
Teaching is organised as follows:
Activity Credits Period Academic staff Timetable
Teoria 4 I semestre Gloria Menegaz

Go to lesson schedule

Laboratorio 2 I semestre Gloria Menegaz

Go to lesson schedule

Learning outcomes

The course aims at providing the students with the fundamentals of signal and image processing with emphasis on aspects that are relevant in the field of bioinformatics at both theoretical and practical levels. At the end of the course the students will be able to analyze the typical signal and image processing problems encountered in bioinformatics as well as to devise and implement suitable solutions grounding on the knowledge gained in the theory sessions and using the main available toolboxes.


The theory part aims at providing the students with all the theoretical aspects that are needed for understanding, analyzing and solving the main signal and image processing issues that are encountered in the field of bioinformatics.
The course contents include the mathematical foundations, methodological tools and algorithms that are required in this respect and will be complemented by exercise sessions.

Introduction to signals and systems with special focus on the biomedical and bioinformatics fields
Linear Time Invariant Systems (LTIS): continuous and discrete time, properties, zero-input, zero-state, impulse response, transfer function, system stability, analysis of system behavior
Fourier Transform (FT): Fourier Series, Continuous and Discrete time FT, Discrete Fourier Transform (DFT)
Filtering: analog and digital, low-pass, high-pass, in time and frequency domain, linear and non-linear, 1D and 2D
A/D signal conversion: sampling and quantization of signals and images
Image segmentation: edge-based and region-based main segmentation algorithms
Texture analysis by Gabor filters and basics of time/frequency and multiscale analysis
Feature extraction in time/space and frequency and application examples in the field of pattern recognition
Please note that all the methods are meant to be applied to both signals and images unless differently specified.

Laboratory sessions at getting familiar with the main algorithms and tools introduced in the theoretical sessions by solving some typical signal and image processing problems.

Assessment methods and criteria

The exam of the SIGNAL AND IMAGE PROCESSING module consists in questions concerning the topics of both the theory and the laboratory sessions, with respective weight of 2/3 and 1/3, and one exercise (15 punti). In case the exam would be in teleconference mode it would be in oral form.