Machine vision removes the physical contact between a test system and the parts being tested, preventing part damage and offering safety and operational benefits by reducing human involvement in a manufacturing process. Machine vision systems also easily inspect object details too small to be seen by the human eye. For industrial applications, machine vision ensures lower costs, high accuracy, robustness, and reliability.
Image contrast and resolution are the most important characteristics that determine image quality in machine vision as well as how successful the corresponding vision system can be for an application. The modulation transfer function (MTF) is what governs both of these characteristics, and each component in the optical train of a vision system contributes to the overall MTF. Optical filters directly influence the contrast of an image. Filters that increase image contrast can also improve image resolution because of this MTF relationship.
This 60-minute Webinar from the editors of Tech Briefs Media Group looks at various applications of machine vision in automation, robotic guidance, verification, and parts inspection/testing, along with the benefits such systems provide. It also demonstrates how enhancing image contrast with high-quality interference filters improves the contrast of images acquired in various machine vision applications.
Topics include the following:
- The impact of non-contact sensors on today’s manufacturing
- How non-contact sensors improve quality, lower costs, and reduce manufacturing time
- How high-quality interference filters improve the contrast of images acquired in machine vision applications
- Why optical interference filters are critical to the overall performance of machine vision applications and should be considered when designing and installing systems
An audience Q&A follows the technical presentation.