Machine Vision

Understanding Machine Vision technology applications; Characteristics of Systems; Vision System Elements, Sensors, and data acquisition; Biological-Based Optical Sensors and Transducers; Machine Vision Importance for Real Mechatronic Applications and Automation; Machine Vision Industry; Machine Vision Concepts and algorithms; Image Acquisition; Image Conversion; Optical Information Processing and Pattern Recognition; Real-Time Feature Extraction and Image Recognition; Feature Selection and Planning for Visual Servoing; Image Processing and Decision-Making; Visual Methods for Monitoring and Detecting; Visual Guidance for Robots; Three-Dimensional Machine Vision Techniques; Evaluating Machine Vision Applications; Application Analysis and Implementation; Alternatives to Machine Vision and trends. Use of AI and Machine Learning at Machine Vision problem solving.

NB! This course will take place in autumn semester 2024/2025 which starts on 2nd of September and ends 26th of January (you can find that information under Start date section). The real course start and end dates will be announced at the beginning of September at the latest.

Knows and orients in basic principles and structures of high-tech machine vision systems and their use in mechatronics, robotics and production systems. Knows the main techniques and methods for machine vision applications and their usability in technology applications. Knows and is able to use design and analysis concepts for developing practical machine vision systems for solving basic related technical problems. Knows and is able to implement machine vision software to automate technology processes on the base of visual information.

Final assessment can consist of one test/assignment or several smaller assignments completed during the whole course. After declaring a course the student can re-sit the exam/assessment once. Assessment can be graded or non-graded. For specific information about the assessment process please get in touch with the contact person of this course. For specific information about grade transfer please contact your home university

MATLAB and Phyton programming, calculus. NB! Presence on campus 2 weeks (dates to be specified).

• Loengukonspekt (lecture slides and exrecise materials)

lectures, practices, exercises