When working with applications in spindles, grippers, and robotics, space is typically very tight. Unfortunately, that fact does not eliminate the need for automation. If anything, it increases it.
Optical technology brings powerful capability to a wide range of problems. Imagine, for example, that you hold a blank piece of white paper up to the night sky.
Optical character recognition (OCR) is an important technique in industrial environments. After all, machine vision makes it possible to reliably identify workpieces and products throughout the entire value chain based on printed or stamped characters.
The new standard in single-link interface speed, 10 Gigabit Ethernet (10 GigE), enables users to take full advantage of the latest generation of high-performance sensors with their higher resolution, frame rates, bit depth and dynamic range.
The term machine vision can imply a computer having a set of eyes for an inspection. To develop a complete solution for machine vision applications, vision engineers execute a series of tasks that usually fall into five categories: plan, design, build, integrate, and validate.
Manufacturers who choose embedded vision for their application will find, in most cases, that the process for setting up the camera is simpler than setting up a traditional pc-based system.
Embedded vision is a term that means slightly different things to different people. When it comes to manufacturers using machine vision for automation and other applications, embedded vision generally refers to smart cameras or smart systems.