Machine Vision Components And Applications In Production Processes

Picking and sorting of objects is an activity few humans look forward to with great elation. However, the

Picking and sorting of objects is an activity few humans look forward to with great elation. However, the tedious nature of the task is a prime candidate for automation using robotics. Beyond the obvious hardware that it takes for a robot to operate within the confines of a designated task, a less obvious one, machine vision, acts as a critical component of efficient robotic sorting. The technologies involved with machine vision, sensing, and object interaction are already being used by robots with great success on the International Space Station in completing even complex tasks, semi-autonomously.

Robotics labs around the world are hard at work refining the technology for applications in factories, warehouses, and even relief efforts in disaster areas. The environment in each example is likely one with an abundance of clutter as well as rife with objects of varying size, weight, and orientation. This is a perfect setting to test and apply the advancements of machine vision and object interaction.

a picture of machine vision in action on an assembly line.

Machine Vision Is Increasingly Relied Upon In Automation To Drive Quality And ROI. The Market Is Expected To Reach $18.7 Billion By 2022.

Components of Machine Vision

Machine vision has significant capabilities on factory floors and production lines. As systems acquire product images and extract the relevant information, the information is analyzed and communicated to the outside world. A lot goes into the technology behind machine vision, which can be broken down into five essential components: lighting, lenses, vision processing, image sensing, and communications.

Machine Vision Lighting

Lighting is essential to the success of machine vision results. By capturing images through analysis of reflected light, machine vision systems can effectively identify objects as well as their orientation in an environment. Several lighting techniques can be utilized by machine vision systems, including backlighting to measure external and edge measurements, structured lightning patterns to interpret angles on an object’s surface, and strobe lighting to freeze moving objects for examination or aid in countering blurring. These are only a few examples of the lighting techniques utilized in machine vision systems, which can also incorporate diffuse dome, bright-field, dark-field, and axial diffuse lighting. A more comprehensive guide to machine vision lighting can be found in this whitepaper from National Instruments.

Machine Vision Lenses

Just as in conventional cameras, lenses capture an image and deliver it to sensors within the camera. One can also think of this in terms of our eyes delivering the images we see to our brains for interpretation. Fixed and interchangeable lenses are the most common types of lenses in machine vision systems. Lenses of varying sizes and shapes are used to capture the most precise image for the system’s intended use. Fixed lenses are typically standalone components and can autofocus based on mechanical adjustment or as a fluid lens that automatically adjusts to deliver the highest quality. These lenses have a fixed field of view from a certain distance. On the other hand, interchangeable lenses are typically equipped with C-mounts or CS-mounts that allow them to be removed or attached at will to the systems they are enhancing. Vision Systems Design does an excellent job detailing the fundamentals of machine vision lenses in this article.

Machine Vision Image Sensors

An essential component of image capture, image sensors utilize a charged couple device (CCD) or a complementary metal oxide semiconductor (CMOS) to interpret light as electrical signals. In more easily digestible language, image sensors capture the reflected light from an image and make sense of the object, interpreting it as a digital image with precise details that aid in accurate measurements by processing software. A more comprehensive article on image sensors from Coventor can be found here.

Vision Processing Units

A Vision Processing Unit (VPU) is another component of machine vision that serves to extract information from the digital images captured by the cameras being used. The processing undertaken by these microprocessors can be completed externally or internally on a standalone system. A process completed over the course of several steps, images will first be acquired from the sensor and software will identify specific features of an image, including measurements and comparisons to reach a decision based on the result. The results are then communicated to the system to complete additional actions. While it is true that the physical components of machine vision are integral to the overall function of these systems, the processing algorithms that evaluate and compare results are the most influential. Processing software is responsible for configuring camera parameters, pass-fail detection, communicating information to factory floors, and supporting Human Machine Interface (HMI) development.

Machine Vision System Communications

As one might conclude from this brief overview of machine vision, these systems are an amalgamation of parts and components that must all work in unison to deliver accurate results consistently and in real-time. Add to this the fact that environments can change dynamically and at a moment’s notice raises necessity to realign vision on the fly. Communications are an essential component of machine vision systems and are typically executed through discrete I/O signals or via data delivered through a serial connection to a connected device, i.e. Ethernet or RS-232 output. Programmable logic controllers (PLC) are the favored connection made to discrete I/O points, which can control stack lights, solenoids or other indicators to trigger reject responses from the system.

Machine Vision Applications In Production Processes

As mentioned above, machine vision is already hard at work on the ISS. However, more candid applications exist right here on Earth. Industrial inspection is among the largest industries utilizing machine vision. However, many applications, such medical imaging, remote sensing, and autonomous vehicles use machine vision on a continuous basis.


Machine vision applications in warehouse and factory conditions are exceptional at mitigating the amount of human error that can affect repetitive processes, such as bin-picking and sorting tasks. The technology allows for robots to make sense of a cluttered workspace or full bin and extract the relevant objects appropriately.

Assembly Verification

When quality is of the utmost importance, consistent outputs on the assembly line are necessary to a company’s bottom line. Inspection operations in assembly verification are completed in milliseconds to ensure that every item is up to spec and incomplete products don’t make it past the check.


Automating production is an essential function of manufacturing operations. Machine vision can assist in detecting system abnormalities, jams, and other hiccups that can affect the production process. Improving the consistency of operations ensures little interruption and a reduction in production costs that result from downtime.

Removing Defects

Automation demands two things: consistency and simplicity. When things get complicated they tend to also get expensive. Machine vision systems are capable of inspecting hundreds of items per minute to a high degree of accuracy, thus ensuring that defective items are removed from the equation before they can affect a business’ bottom line, without the need for complex systems of checks throughout the production process.


The ability to scan barcodes and other identifying under several difficult conditions, be it lighting, texture, or packaging, is essential to keep operations running smoothly. Machine vision systems help achieve optimum efficiency in quickly reading necessary labeling information on the production line and in distribution centers.

About Encompass Solutions

Encompass Solutions is a business and software consulting firm that specializes in ERP systems, EDI, and Managed Services support for Manufacturers and Distributors. Serving small and medium-sized businesses since 2001, Encompass modernizes operations and automates processes for hundreds of customers across the globe. Whether undertaking full-scale implementation, integration, and renovation of existing systems, Encompass provides a specialized approach to every client’s needs. By identifying customer requirements and addressing them with the right solutions, we ensure our clients are equipped to match the pace of Industry.

Sean Balogh

About Sean Balogh

A marketing professional working hard to deliver relevant and engaging content to audiences in education, technology, and manufacturing.