Computer Vision and Multimedia

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Motivation and exhibition of the topics in the Lectures, including interactive solving of exercises and examples
applied to real world problems and systems.
Laboratory experiments in the Practical-Laboratory classes, including two small projects: one in the vision module
and one in the multimedia module. The experiments and projects are organized in groups of two students with a
per-group report and an individual assessment. Attendance is mandatory in these classes (2 absences maximum).
The ECTS organization considers 97 semester hours for student autonomous work.
Evaluation: final written exam: 12 points (60% total) – min. 40%. Laboratory experiments and projects, associated
reports and individual assessment: 8 points (40% total) min. 50% per module.
For the students with extra legal rights associated with their Student-Worker status, and for the components with
mandatory attendance and distributed evaluation, an alternative for the rules associated with these components
can be found.

Learning objectives:
To understand the principles of image formation, acquisition and representation;
To understand and apply the most representative image processing techniques in the spatial domain;
To understand basic techniques for color and texture representation and processing; To develop industrial
computer vision applications using dedicated software;
To understand: the digital representation of audio and video signals; the basic principles of information theory; the
main techniques and standards for compression, coding, storage and transmission of image, audio and video
signals.
Generic learning outcomes and competences-the learner is expected to be able to:
Use computer vision acquisition devices and processing techniques to develop industrial computer vision
solutions using dedicated software;
Participate in multimedia development and installation projects, involving stand alone or networked image, audio
and video equipment, such as in video-surveillance applications.

Part I – Computer Vision:
Computer vision objectives;
The Human Visual System;
Sensors and representation of images;
Fundamentals of digital images;
Analysis of binary images;
Image processing in the spatial domain;
Gray level transformations;
Histogram-based processing;
Processing using logical operators;
Filtering – smoothing and sharpening;
Elements of digital morphology: dilation, erosion, opening and closing;
Understanding color and texture;
Introduction to segmentation;
Application examples.
Part II – Multimedia:
The Multimedia concept;
Digital representation of audio and video signals;
Principles of information theory;
Image compression techniques;
Principles of audio compression;
Principles of video compression;
Main techniques and standards for representation, compression, coding, storage and transmission of multimedia signals;
Application examples.

NAO