Vision & Sensors

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The official definition of “machine vision” encompasses all industrial and nonindustrial applications in which a combination of hardware and software provide operational guidance to devices in the execution of their functions based on the capture and processing of images. In short, machine vision helps companies manufacture quality goods, repeatably.

Human perception is the ultimate standard for determining the visual quality of a device. However, the use of human inspection as a quality control method for development or production of devices is problematic because of the statistical variation between observers.

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.