35504 - Fundamentals of Image Processing

Course Unit Page

  • Teacher Raffaele Cappelli

  • Credits 6

  • SSD ING-INF/05

  • Language Italian

  • Campus of Cesena

  • Degree Programme First cycle degree programme (L) in Computer Science and Engineering (cod. 8615)

Academic Year 2018/2019

Learning outcomes

At the end of the course, the student has got the basic knowledge on the main algorithms and techniques for digital image processing.

Course contents

  • Introduction to digital images
  • Color models
  • Basic transformations: pixelwise, local, and global
  • Digital filters and convolution
  • Edge extraction and segmentation
  • Digital topology and mathematical morphology


R. C. Gonzalez e R. E. Woods, Digital image processing, 3rd Edition, Prentice Hall, 2008.

Teaching methods

  • Lectures
  • Guided exercises at the PC

Assessment methods

Learning results are assessed through a written test of 90 minutes, during which it is not allowed to use books, notes, or any electronic device. The examination aims to assess the achievement of the following learning objectives: 1) detailed knowledge of the image processing algorithms discussed during the course; 2) ability to implement such algorithms and apply them in software programs; 3) understanding of the main functionalities of the class library used during the lab exercises. To this end, the written test contains both theoretical questions and practical exercises, which ask the student to implement algorithms or portions of algorithms of image processing in C #, exploiting also some functionalities of the class library used during the lab exercises.

Teaching tools

  • Lecture notes (Available here)
  • C# classes to be used in the lab exercises

Office hours

See the website of Raffaele Cappelli