Last updated: 1 May 2025

What is machine vision?

Like we like to say machine vision is the eyes of a machine, like giving a machine human eye, but with much more accuracy and faster. Machine vision allows machines to see by using machine vision cameras and computer software that analyses the captured images which then will allow to recognize objects, take measurements and make decisions based on what the machine is seeing.

History of machine Vision

1950's

Machine Vision began with early computer vision research that focus on understanding and replicating human vision in machines.
1960's

Two-dimensional imaging was developed for statistical pattern recognition. Studies begin for 3D machine vision.
1970's

First practical applications such inspections and quality control, specialized hardware began to emerge, pattern recognition became more refined.
1980's

OCR systems, automated inspections were increasingly used. CCD cameras became common, allowing higher quality images. Vision software began to evolve. More accessible vision systems.
1990's

Integration of machine vision with robotics, developing more advance automation systems. Integration of machine vision and artificial intelligence started to emerge.
2000's

Advance camera technology, rise of deep learning. Machine Vision is now widely used across industries such as automotive, healthcare, agriculture, security, etc.

Key components of a machine vision system

The heart of a machine vision system is of course the camera, but without these other components the system would not be completed:

Machine Vision Camera - The protective enclosure housing a lens mount, an image sensor, a processor, power electronics and a communication interface.
Machine Vision Lens - Enables the camera to capture a clear view of what you would like to see.
Industrial Cable - Depending on your interface, the cable will power the camera as well as transfer the data. Other cables can be used for triggering lighting.
Machine Vision Lighting - When the camera captures an image of an object, it is capturing the light reflected by this object. The amount of light that is absorbed or reflected will depend on the object's surface whether it is translucent, opaque or transparent.
Housing and Accessories - We carry an amazing IP67 camera housing for harsh conditions, we also have different accessories for special projects.
Computer Vision Software - While the hardware is responsible for capturing the image and sending it to the host PC, the vision software is responsible for analyzing the captured data and interpreting it to perform a specific task.

Here at VA Imaging, we offer everything you need from one single trusted source. The workflow of a machine vision system is image capturing and pre-processing, feature analysis and extraction, decision-making and output generation as well as integrating this with other systems such PLCs and robotics.

Core Technologies behind machine vision

Machine Learning and Artificial Intelligence

Using AI and Machine Vision together will enhance automation, boost efficiency and improve quality control. AI is easier to integrate, upgrading us also simpler. Vision AI and machine learning can reduce price, improve quality and ultimately be more profitable.

Deep Learning Techniques

Deep Learning can improve the accessibility and effectiveness of machine vision systems. Deep learning can identify shapes, patterns, and specific objects in an image which will then process the data, extract features and make fast and reliable decisions.

Some Machine Vision Applications

Quality Control and Defect Detection: Our high-resolution cameras have the advantage of process an image which will identify surface defects, anomalies, dimensional variations, etc.
Robotics and guidance: With machine vision we can guide robots which then will perform complex precise tasks, such pick and place, assembly or welding. They can also help with guiding by adapting positions.
Barcode reading and Optical character recognition: Machine Vision can read and decode barcodes, QR codes, serial numbers as well as accurately recognise texts, characters, symbols. This will reduce errors and improve efficiency.
Medical imaging and diagnostics: This application can help detect conditions by reading images such X rays or different types of scans.

These are just some of the many machine vision applications we can support. In the following link: Machine Vision Solutions & Applications. You can find many other applications such golf and other sport analysis, security inspections, object detections, among many others.

Conclusion

In conclusion, we can say that machine vision is the advanced technology that allows machines to see and understand visual data, similar to our human vision. It has a wide range of applications in multiple industries which have been transformed by automating tasks such object recognition, inspection and quality control. The use of machine vision is a powerful tool that has improved efficiency, productivity and accuracy. As technology advances, machine vision will also continue to evolve and expand today’s capabilities which will make an essential component for modern industrial and technological innovation.