What is machine vision?
A Quick Guide to Machine Vision
What Is Machine Vision?
Machine Vision uses industrial cameras, lenses, light sources, and image processing software to give
equipment the ability to "see" and "judge" products. Based on pre-configured criteria, the system can
automatically determine whether a product meets specification, completing inspection, measurement,
and classification on high-speed production lines.
Compared with manual visual inspection, machine vision offers faster speed, consistent judgment, and
stable long-term operation. It is now widely used across the semiconductor, electronics, food, medical,
automotive parts, logistics, and packaging industries.
How Does Machine Vision Work?
A complete machine vision system typically consists of the following five steps:
Lighting
Use suitable lighting to illuminate the object under inspection, clearly revealing product features such as
scratches, cracks, printed text, or dimensional outlines.
- Image Acquisition
An industrial camera paired with a lens captures the product image and transmits it to a computer or vision
controller.
- Image Processing
Algorithms perform filtering, edge detection, grayscale analysis, contour extraction, feature recognition, and
other processing to improve inspection accuracy.
- Inspection
Based on pre-set standards or an AI model, the system compares whether the product meets specification
— for example, whether dimensions are correct, whether there are scratches, or whether printed text is
complete.
- Control
When the system determines a product is defective (NG), it can immediately send a signal to a PLC or
robotic arm to automatically reject, sort, or stop the equipment — enabling fully automated production.
What Equipment Does a Machine Vision System Need?
A complete system typically includes:
- Industrial Camera
- Industrial Lens
- LED Lighting
- Light Controller
- Frame Grabber (depending on interface requirements)
- Vision Controller or Industrial PC (IPC)
- Vision Software or AI Algorithms
- PLC or Automation Equipment
Equipment combinations vary depending on the specific application requirements.
What Are the Applications of Machine Vision?
1. Surface Defect Inspection
Checks products for surface defects such as scratches, cracks, dents, stains, or chipping.
2. Dimensional Measurement
Measures length, diameter, height, hole diameter, spacing, and other dimensions, improving measurement
efficiency and consistency.
3. OCR / OCV Character Recognition
Reads lot numbers, serial numbers, production dates, barcodes, or QR codes on products, and verifies that
the content is correct.
4. Positioning & Guidance
Provides precise coordinate positions for robotic arms or automated equipment, used for pick-and-place,
assembly, or positioning.
5. Color Recognition
Determines whether a product's color meets specification — for example, bottle caps, labels, parts, or
packaging.
6. Foreign Object Detection
Checks whether foreign objects have been mixed into food, pharmaceuticals, or packaging, improving
product safety.
Why Do Companies Adopt Machine Vision?
Adopting machine vision brings a range of benefits:
- Improved product quality and consistency
- Lower manual inspection costs
- Continuous 24-hour inspection
- Reduced missed defects and false judgments
- Higher production efficiency and yield
- Complete inspection image records and quality traceability
- Supports smart manufacturing and Industry 4.0
Which Industries Are Suited to Machine Vision?
Machine vision is already widely used in:
- Semiconductor & wafer manufacturing
- PCB & electronic components
- Food & beverage packaging
- Medical devices
- Automotive parts
- Metal processing
- Plastic injection molding
- Lithium batteries & new energy
- Logistics & warehousing
- Optoelectronics
How to Choose the Right Machine Vision System?
Requirements for lighting, cameras, lenses, and algorithms vary by inspection task. Before planning,
it's recommended to confirm:
What features need to be inspected?
What is the product's size and material?
How fast is the production line?
What level of precision is required?
Is installation space on-site limited?
Does it need to integrate with a PLC, robotic arm, or MES system?
A thorough requirements analysis and testing process is the key to building a machine vision solution
that balances stability, efficiency, and cost-effectiveness.
Conclusion
Machine vision is more than just "taking a picture" — it's the integration of optics, image processing,
and automation control that gives equipment fast, stable, and consistent inspection capability. As AI
technology continues to advance, machine vision is increasingly becoming a core pillar of smart
manufacturing, helping companies improve quality, reduce costs, and build more competitive
production processes.
If you'd like to find the right machine vision solution for your production line, feel free to contact InRay.
We can provide professional evaluation and integration recommendations based on your product
characteristics and production requirements.