Machine vision, made simple: how OMRON makes vision easier to deploy
Published on 06 October, 2026 in Brand Protection
Machine vision has a reputation for being complicated. And for good reason. Traditional vision systems can involve cameras, lighting, lenses, software, programming and a fair amount of specialist knowledge. For machine builders, that can make adding vision to an application feel like taking on a whole new engineering challenge. But it doesn't always have to be that way.
Advances in AI-based vision are making inspections easier to set up, easier to adapt and more accessible to manufacturers that may previously have considered vision too complex or expensive.
So, where can machine vision actually make a difference? What has changed? And how straightforward can it really be to get an inspection up and running?
Let's take a look.
Four problems machine vision can help solve
Before thinking about cameras, software or AI, it's worth taking a step back and looking at the problem you're trying to solve.
Across the applications we typically see, four inspection challenges come up again and again:
1. Defective products reaching the market
A missing component, damaged part or incorrectly assembled product can quickly become a quality issue. Automated inspection can check products consistently and identify problems before they leave the production line.
2. Parts entering a process in the wrong state
A component might be missing, incorrectly positioned or the wrong type altogether. Detecting these issues early can prevent them from causing bigger problems further down the line.
3. Unplanned stops and lost throughput
If an issue isn't detected until later in the process, it can lead to stoppages, rework or wasted production time. Catching problems at the point where they occur can help keep production moving.
4. False rejects
Automation isn't useful if good products are continually being rejected. A reliable vision system needs to distinguish between genuine defects and acceptable variation, helping manufacturers protect both quality and yield.
Why did vision become so complicated?
The challenge is that getting there can require time and expertise.
A typical application might involve selecting the right camera and lens, configuring lighting, programming inspection tools, setting thresholds and rules, and then fine-tuning everything until the system can reliably tell a good product from a bad one.
For experienced vision engineers, that's part of the job.
For a machine builder who simply needs to check whether a component is present or whether two product variants are different, it can feel like a lot of technology for a relatively simple problem.
This is where AI-based vision is changing the conversation.
AI is making machine vision more accessible
That makes them particularly useful for applications where the difference between a good and bad product isn't always easy to describe with a set of rules.
Think about a cosmetic defect, for example. You might be able to look at a product and immediately see that something doesn't look right. Describing exactly what makes it "wrong" in a way that a conventional vision system can understand can be much harder.
An AI-based system takes a different approach. Rather than telling it exactly what every defect looks like, you can train it using examples.
This doesn't mean AI replaces conventional vision. There are still applications where traditional, high-end vision systems are the right choice.
But for simpler inspections, AI can remove some of the complexity that has traditionally been associated with machine vision.
And in some applications, an AI-based approach can cost less than half that of an equivalent conventional rule-based system, although the actual saving depends on the application and the number of cameras required.
One camera. Everything you need.
Depending on the model, this can include the optics, autofocus, lighting, image processing and software needed to perform the inspection.
That means less time spent selecting and configuring individual components, and less equipment to integrate into the machine.
For machine builders, that's important.
The simpler the hardware and software setup, the easier it becomes to incorporate vision into a machine without creating unnecessary engineering work.
So, what can AI vision actually inspect?
Many inspections can be grouped into three straightforward questions:
1. Is it there?
Is the component present?
But how easy is it to deploy?
It's one thing to say that AI vision is simpler. It's another to actually get a working inspection running on a machine.
With OMRON's approach, the process is designed to be straightforward.
Once the camera is connected and you have an image, a basic inspection can take just five to ten minutes to configure.
For a defect inspection, there is an additional annotation step. You provide examples and identify the areas the system needs to learn from before training it to recognise the difference between acceptable and defective products.
Even then, a straightforward defect application can be up and running within around 30 minutes.
See it in action
In our Two Minutes to Vision demonstration, we take an AI-based smart camera through the setup process, from capturing good and bad images through to annotation, training and checking the results.
The workflow can be broken down into seven simple steps:
Capture → Select → Annotate → Train → Inspect → Check → Adjust
The system can also provide tools such as a histogram to help assess the results and understand how confidently the inspection is distinguishing between good and bad products.
The result is a much more approachable way of working with machine vision.
Instead of spending a long time programming an inspection before you know whether it will work, you can quickly test the concept, see the results and refine it from there.
What does this mean for machine builders?
It's that machine vision becomes a more realistic option for applications where it may previously have been ruled out.
If you've ever looked at a vision requirement and thought:
It may be worth looking at what's now possible.
AI-based smart sensors won't replace every type of vision system. Complex applications still need sophisticated technology and expertise.
But for many straightforward inspection tasks, the barrier to entry is getting lower.
And that gives machine builders another tool for improving quality, reducing manual inspection and catching problems earlier in the process.
Ready to explore your application?
OMRON can help you evaluate your inspection, explore what an AI-based approach can achieve and develop a proof of concept, free of charge.
You don't need to know exactly which camera or inspection method you need before you get started. Bring us the problem you're trying to solve, and we can help explore the options.
Take a closer look
Want to see just how straightforward AI-based machine vision can be?
Watch our on-demand Two Minutes to Vision webinar to see the technology in action, including AI vision and advanced code reading.
