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CODE 52644
ACADEMIC YEAR 2022/2023
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR ING-INF/03
LANGUAGE Italian
TEACHING LOCATION
  • GENOVA
SEMESTER 2° Semester
TEACHING MATERIALS AULAWEB

OVERVIEW

Starting from their representation, the teaching of PROCESSING OF HISTORICAL-ARTISTIC DIGITAL IMAGES introduces the basic techniques for the analysis and transformation of digital images. Large space is devoted to issues related to reproduction and color analysis. The main algorithms introduced during the lessons are deepened during practical laboratory exercises.

AIMS AND CONTENT

LEARNING OUTCOMES

To give basic knowledge of digital representation of historical-artistic images and of their computerised elaboration with the aim of analysis of quality, restoration and compression

Particular attention will be paid to the methods of teaching.

AIMS AND LEARNING OUTCOMES

 

In addition to learning the basic techniques of digital image analysis and processing, students acquire the tools they need to be able to creatively use some image transformation programs and keep up-to-date with developments in the application domain

TEACHING METHODS

Lectures with the help of Power-point presentations and delivery of transparencies to students. Laboratory exercises at the School of Engineering.

Classes are held in person. Attendance, although not compulsory, is recommended. The lecturer, at the specific request of a student (by e-mail), may allow him/her to follow classes remotely via “Teams” platform and to view class recordings.

SYLLABUS/CONTENT

Programme for students taking the course for 6 cfu

Digital images and their representation: acquisition of an image, digital representation (sampling and quantisation), representation of colour (chromatic information), basic mathematical tools.

Evaluation of the quality of a digital image: contrast, presence of noise or geometrical distortion.
Improvement of images: reduction of noise, increase of contrast, reduction of geometrical distortion, elements of elaboration in the frequency dominion.
Restoration of images: elements of quantitative restoration techniques, virtual restoration methods.

Analysis of images and extraction of structures: extraction of contours and linear primitives, segmentation, analysis of structure.

Compression of images: codifying with and without loss, predictive coding, coding based on transformation, general description of some standard formats of compression.

Application to art work images: objective knowledge, conservation and restoration.

The course also involves computer exercises using software to elaborate images and applying software to art work images.
Il corso prevede esercitazioni a calcolatore mediante l'uso di pacchetti software per elaborazione di immagini e la loro applicazione ad immagini di opere d'arte

RECOMMENDED READING/BIBLIOGRAPHY

S. DELLEPIANE, Elaborazione di immagini digitali, ECIG, 2004.

C. OLEARI, Misurare il colore, Hoepli, II edizione, 2008

W. K. PRATT, Digital image processing, Wiley Interscience, 3a edizione, 2001.

R.M. HARALICK , L:G: SHAPIRO, Computer and Robot Vision, Vol. 1, Addison-Wesley, 1991.

P. ZAMPERONI, Metodi dell'elaborazione digitale di immagini, Masson, 1990.

D. H. BALLARD, C. M. BROWN, Computer vision, Prentice Hall, 1982.

TEACHERS AND EXAM BOARD

Exam Board

SILVANA DELLEPIANE (President)

GABRIELE MOSER

FEDERICA FERRARO (Substitute)

LESSONS

LESSONS START

Lessons will start on February 15, 2023.

EXAMS

EXAM DESCRIPTION

Oral exam with lab practice exercise test.
 

ASSESSMENT METHODS

Oral exam and practical test with a computer

Exam schedule

Data appello Orario Luogo Degree type Note
18/01/2023 15:00 GENOVA Orale
08/02/2023 15:00 GENOVA Orale
10/05/2023 15:00 GENOVA Orale
31/05/2023 15:00 GENOVA Orale
28/06/2023 15:00 GENOVA Orale
19/07/2023 15:00 GENOVA Orale
13/09/2023 15:00 GENOVA Orale