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DIGITAL IMAGE PROCESSING

CODE 104782
ACADEMIC YEAR 2022/2023
CREDITS
  • 5 cfu during the 2nd year of 10378 INTERNET AND MULTIMEDIA ENGINEERING(LM-27) - GENOVA
    		•
    SCIENTIFIC DISCIPLINARY SECTOR ING-INF/03
    LANGUAGE English
    TEACHING LOCATION
  • GENOVA
    		•
    SEMESTER 1° Semester
    MODULES This unit is a module of:
    TEACHING MATERIALS AULAWEB

    AIMS AND CONTENT

    LEARNING OUTCOMES

    In this course the basic techniques of digital signal and image processing are presented and their application to signals and images from real domains are discussed: • Digital Image Representation and Color Spaces • Image Filtering (linear and non-linear) • Edge Detection • Image Segmentation • Texture Analysis • Mathematical Morphology • Moments and Hough Transform • Adaptive Processing, Multiscale, Data Fusion

    AIMS AND LEARNING OUTCOMES

    The course provides an introduction to digital image processing techniques. Analysis of digital images has several important applications e.g. remote sensing, biomedical imaging, telecommunications, character recognition, advertising photography, historical objects analysis. Nowadays, the available computational power allows almost everyone to leverage on high-performance algorithm for image processing.

    In the first part, digital images will be introduced. Several color spaces are described and common techniques to change from one to another are provided.

    Basic methods are presented, e.g. contrast enhancement, thresholding, histogram analysis, noise reduction, underlining the use of the discrete Fourier transform (DFT).

    Classical techniques for edge detection, segmentation, mathematical morphology analysis, texture analysis are topics of the course.

    During practical lessons, software for image processing such as GIMP, ImageJ, MatLab and libraries such as come OpenCV are used.

    TEACHING METHODS

    Combination of classical lessons and laboratory exercises.

    SYLLABUS/CONTENT

    • Digital Image Representation
    • Color Spaces
    • Image Filtering (linear and non-linear)
    • Edge detection
    • Image Segmentation
    • Mathematical morphology
    • Moments and Hough Transform
    • Texture analysis

    RECOMMENDED READING/BIBLIOGRAPHY

    • Jhane, B., Digital Image Processing, Sprinter, Berlin, 1997 
    • Dellepiane S.,  (2004), Elaborazione di immagini digitali – Materiale di supporto alle lezioni ed Esercizi. GENOVA: ECIG, ISBN: 88-7544-017-4
    • Class slides can be downloaded from aulaweb. 
    • Tests and solutions can be downloaded from aulaweb.

    TEACHERS AND EXAM BOARD

    Exam Board

    SILVANA DELLEPIANE (President)

    FEDERICA FERRARO

    MATTEO PASTORINO

    ANDREA RANDAZZO

    SEBASTIANO SERPICO

    ALESSANDRO FEDELI (President Substitute)

    GABRIELE MOSER (President Substitute)

    LESSONS

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    • Written test
    • Laboratory exercises attendance verification

    Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities

    ASSESSMENT METHODS

    Written examination

    Exam schedule

    Date Time Location Type Notes
    11/01/2023 15:00 GENOVA Scritto Please refer to the new exam dates: - January 25, 2023. - February 16, 2023
    03/02/2023 15:00 GENOVA Scritto Please refer to the new exam dates: - January 25, 2023. - February 16, 2023
    06/06/2023 15:00 GENOVA Scritto Please refer to the new exam dates: - January 25, 2023. - February 16, 2023
    05/07/2023 10:00 GENOVA Scritto
    06/07/2023 15:00 GENOVA Scritto Please refer to the new exam dates: - January 25, 2023. - February 16, 2023
    06/09/2023 15:00 GENOVA Scritto Please refer to the new exam dates: - January 25, 2023. - February 16, 2023