Industrial machine vision cameras and sensors are finding their way into applications both on and off the manufacturing floor.

When an engineer begins the process of specifying a new machine vision system, they will often think very carefully about the line speed, the optics, and the image processing software.

You’ve learned about light sources, lenses, cameras, camera interfaces, and image processing software. Now, you may be wondering exactly how to design and implement a complete, successful machine vision system. 

In the world of machine vision, as in any tech field, there is a distinct divide between hardware and software. The hardware includes components of machine imaging systems such as the physical camera, lensing, cable interfaces, the PC or processor, etc. and are defined by rigid specifications (i.e. resolution of a camera, processing power, bandwidth of interface). 

Frame grabbers are essential components in machine vision systems that provide ultra high-speed, high-data image capture from one camera or multiple cameras simultaneously. 

Machine vision systems consist of a number of component parts and all of these must be optimized for the best possible performance. Choosing the right cables and connectors to link cameras to a vision system or PC is one important part of this and is driven by the particular application.

Choosing the right interface for your machine vision application is a key decision in your camera selection process. The following sections provide an overview of the different types of cables and connectors available for machine vision applications along with associated pros and cons.

The successful application of machine vision technology involves an intricately and carefully balanced mix of a variety of elements.

Where rule-based machine vision has not been attempted or has reached its limits, there is a high potential for deep learning algorithms to support employees and drive forward automation.

At its simplest, automation means to make something automatic. In manufacturing, whether describing a single device or an entire system or process, automation refers to performing one or many tasks autonomously with minimal or even no human interaction in a manufacturing or production environment.