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Computer Vision
Computer Vision
Explore the main topics related to computer vision: from its components (cameras, optics, illumination systems, and image processing software) to their purpose and operating principles.
Course description
The aim of the course is to provide students with the basic knowledge required to navigate the complex field of 2D and 3D industrial computer vision, for measurement and object recognition applications. All the components that compose a vision system will be analyzed in detail, illustrating their operating principles and objectives. The course will therefore cover:
- the main types of cameras, with a focus on how digital images are generated;
- the operating principles of optics and the parameters associated with them (aperture, focus, depth of field, etc.);
- the most common illumination techniques, highlighting the advantages and limitations of each;
- the most widely used software methodologies (classical computer vision or AI-based vision) for extracting information (measurement or classification) from digital images.
This MOOC was produced as part of the Edvance project – Digital Education Hub per la Cultura Digitale Avanzata. The project is funded by the European Union – Next Generation EU, Component 1, Investment 3.4 “Didattica e competenze universitarie avanzate".
Intended Learning Outcomes
Upon successful completion of the course, students will be able to:
- Understand and describe the main components of computer vision systems and their operating principles.
- Design a vision system starting with predefined application requirements.
- Select and justify appropriate optics, illumination, and camera components for industrial vision tasks.
- Convert and validate vision-based measurements through metrological verification and camera calibration.
- Apply independent judgment in the design, evaluation, and validation of computer vision solutions, communicating technical choices effectively.
Prerequisites
No formal knowledge is required.
Activities
In addition to accessing the course content, which consists of videos and other types of online resources, you will be able to discuss and exchange ideas on the MOOC topics with other participants through the forum. The forum is open-access and is not moderated by the instructor. You can use it to engage with other participants or to propose discussions related to the course content.
Furthermore, the various lessons will also include external links to carry out preparatory activities related to the topics covered in the course.
Section outline
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In Week 1, we will begin discussing cameras and sensors.
We will understand how they work, how they are structured, and we will analyze several aspects related to the resulting digital images.
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In Week 2, we will focus on lenses and optics. We will study how lenses work through geometric optics, then move from lenses to objectives, analyzing the main parameters that regulate the characteristics of the resulting digital images.
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Welcome to Week 3 of the Computer Vision course.
After exploring the role of cameras and optics, we will focus on a fundamental element for ensuring high-quality images: illumination.
Illumination is an integral part of light signal conditioning in a vision system. An appropriate choice of the light source can drastically improve image quality by increasing contrast and reducing artifacts that could compromise image analysis.
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After exploring the structure and fundamental principles of vision systems in the previous weeks, we will now delve into the practical aspects of their implementation and the processing of digital images.
During this week, we will focus on three key topics:
- Definition of a vision system: How to design an effective system by selecting the appropriate hardware and optical components.
- Image processing techniques: Tools and methods for extracting information from images.
- Camera calibration: Converting measurements from pixels into real-world units.
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Welcome to the final quiz of the Computer Vision course!
This test is designed to thoroughly assess your knowledge of the principles, technologies, and applications of computer vision systems.
Take the time to carefully read each question before answering.
Objective: Demonstrate that you have acquired a solid understanding of the techniques and methodologies underlying a modern computer vision.
Are you ready to test your knowledge? Start the quiz and good luck!
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Video transcripts Folder
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Assessment
Your final grade for the course will be based on the results of your answers to the assessed quizzes. You have an unlimited number of attempts at each quiz, but you must wait 15 minutes before you can try again. You will have successfully completed the course if you score 60% (or higher) in each one of the assessed quizzes. The maximum score possible for each quiz is given at the beginning of the quiz. You can view your score in the quiz on your last attempt or on the 'Grades' page.
Your final grade for the course will be based on the results of your answers to the assessed quizzes. You have an unlimited number of attempts at each quiz. You will have successfully completed the course if you score a total of 60% (or higher) in all assessed quizzes.
The maximum score possible for each quiz is given at the beginning of the quiz. You can view your score in the quiz on your last attempt or on the 'Grades' page.
Certificate
You can achieve a certificate in the form of an Open Badge for this course, if you reach at least 60% of the total score in each one of the assessed quizzes and fill in the final survey.
Once you have completed the required tasks, you will be able to access ‘Get the Open Badge’ and start issuing the badge. Instructions on how to access the badge will be sent to your e-mail address.
The Badge does not confer any academic credit, grade or degree.
You can achieve a certificate in the form of an Open Badge for this course, if you obtain, at least, 60% of the total score in the graded quizzes and by filling in the final survey.
Once you have completed the required tasks, you will be able to access ‘Get the Open Badge’ and start issuing the badge. Instructions on how to access the badge will be sent to your e-mail address.
The Badge does not confer any academic credit, grade or degree.
Information about fees and access to materials
The course is delivered in online mode and is available free of charge.
Course faculty
Simone Pasinetti
Teacher
Contact details
If you have any enquiries about the course or if you need technical assistance please contact pok@polimi.it. For further information, see FAQ page.