Local, instructor-led live Machine Vision (MV) training courses demonstrate through interactive discussion and hands-on practice the fundamentals and applications of Machine Vision.
Machine Vision training is available as "onsite live training" or "remote live training". Brighton onsite live Machine Vision trainings can be carried out locally on customer premises or in NobleProg corporate training centres. Remote live training is carried out by way of an interactive, remote desktop.
NobleProg -- Your Local Training Provider
Learn Machine Vision in our training center in Brighton.
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping centre and the seafront. Queensberry House, which offers some sea views, is in the heart of the business district in this city. Brighton is a highly sophisticated and modern resort with a thriving economy and tourist industry. Millions of visitors flock here every year, both for leisure and to attend conferences and exhibitions at the Brighton Centre, one of the largest...
Pattern Matching is a technique used to locate specified patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not.
Audience Engineers and developers seeking to develop machine vision applications Manufacturing engineers, technicians and managers
Format of the course This course introduces the approaches, technologies and algorithms used in the field of pattern matching as it applies to Machine Vision.
Marvin is an extensible, cross-platform, open-source image and video processing framework developed in Java. Developers can use Marvin to manipulate images, extract features from images for classification tasks, generate figures algorithmically, process video file datasets, and set up unit test automation.
Some of Marvin's video applications include filtering, augmented reality, object tracking and motion detection.
In this course participants will learn the principles of image and video analysis and utilize the Marvin Framework and its image processing algorithms to construct their own application.
Audience Software developers wishing to utilize a rich, plug-in based open-source framework to create image and video processing applications
Format of the course The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks which allow them to practice the concepts learned. By the end of the class, participants will have developed their own application using the Marvin Framework and libraries.
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