Articles Tagged with ''machine vision''

Several critical components need to come together to form a machine vision system. This includes the sensor (typically within a camera) that captures a picture for inspection, the processing hardware (a PC or vision appliance) and software algorithms to render and communicate the results. In addition, lighting, staging, and lenses are required to set up a machine vision system.

For the past few decades, consumers have rewarded companies that customize their products and services to individual tastes and needs.

You have probably heard, and perhaps experienced, that lighting is a big challenge in applying machine vision and a vital key to its successful application. 

Much of the latest news surrounding machine vision is about machine learning and the innovations regarding algorithms. But those algorithms need data to perform correctly. The data in this case is the images. It is imperative to capture the best image possible so that the algorithms can perform at their highest level.

Imaging lenses are critically important components for systems deployed in all types of environments such as factory automation, robotics, and industrial inspection.

Many of today’s industrial software applications are designed to run natively on the Windows platform. Accessing and controlling external hardware devices with a Windows application is usually achieved by using a driver provided by the hardware supplier and activating hardware functions using an SDK.

While early adopters found more promise than productivity, Industry 4.0 has finally come of age.

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.