Lens and camera sensor technology tends to co-evolve. As cameras drive to smaller and smaller pixel sizes with growing formats, lenses need to be designed to match those higher capabilities. 

In today’s manufacturing environment, automatic vision inspection has been widely applied in many different industries including semiconductor, electronics, food and beverage, pharmaceutical packaging, automotive, and many others.

Understandably, designers of high-throughput, multi-camera machine vision systems have grown dissatisfied with those aging standards and have found a new champion, CoaXPress (CXP), a high-speed, point-to-point, serial communications interface that runs data over off-the-shelf 75Ω coaxial cables.

Trying out different behaviours is one of the classic learning methods. Success or failure decides which behaviour is adopted. This principle can be transferred to the world of robots.

Machine vision processes have become standard practice in quality assurance. Inspecting reflective surfaces, however, presents a challenge. A technology known as deflectometry can be used to reliably detect all types of defect even in these circumstances.

In the past, the amount of processing power necessary to perform color-based machine vision applications was often an insurmountable hurdle. Even when manufacturers did offer color vision, they would typically convert images to grayscale prior to analysis—a strategy that significantly reduces precision and fails to detect edges defined by similar colors.

Lighting and lighting control is a critical component of any machine vision system since it has a massive influence on the signal to noise ratio and contrast in the images acquired.

Sensors that report a factory’s performance by measuring machine functioning, downtime, and production goals are in high demand.

Thermal imaging can be used for quality control in many industries. It is a nondestructive inspection method, which is especially used to detect flaws that are not visible on the surface.