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
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 Bioinformatica - Enrollment from 2025/2026The 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
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2° Year activated in the A.Y. 2018/2019
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3° Year activated in the A.Y. 2019/2020
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One course to be chosen among the following2 courses to be chosen among the following| Modules | Credits | TAF | SSD |
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One course to be chosen among the following2 courses to be chosen among the followingLegend | 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.
Signal and image processing for bioinformatics (2019/2020)
Teaching code
4S003710
Credits
12
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Immagini teoria
Segnali teoria
Immagini laboratorio
Segnali laboratorio
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
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Part 1: Signal processing - Theory
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- 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
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Part 1: Signal processing - Lab
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The Lab activity will consist in solving exercises in Matlab concerning the topics covered during the lessons.
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Part 2: Image processing - Theory
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- 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
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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
| Activity | Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|---|
| Immagini teoria | Rafael C. Gonzalez and Richard E. Woods | Digital Image Processing (Edizione 4) | Prentice Hall College Div | 2017 | 0133356728 | |
| 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 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.
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Part 1: Signal processing - Theory
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Written exam on the topics covered during the course.
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Part 1: Signal processing - Lab
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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.
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Part 2: Image processing - Theory
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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.
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Part 2: Image processing - Lab
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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.
