1. What is Machine Vision?

Machine Vision, also known as machine vision, is a field of computer science and artificial intelligence that focuses on helping computers “see” and “understand” the world through images and videos. Machine Vision uses image processing techniques such as filtering, segmentation, recognition, and classification to create models and algorithms. This technology is applied in many industries, from manufacturing, security, healthcare, transportation to robotics.

Some common applications of Machine Vision include: automatic product quality inspection, object detection and classification, face recognition, motion tracking, and autonomous driving assistance.

2. How Machine Vision works

Machine Vision works based on the principles of digital image processing and artificial intelligence, through a specific process consisting of many steps:

Step 1: Data Collection

Machine Vision collects image data from sources such as cameras, videos or sensors, which serves as the foundation for subsequent analysis.

Step 2: Data Preprocessing

The initial collected data often has noise and uneven brightness, which needs to be processed to remove noise and normalize the lighting before analysis.

Step 3: Image Segmentation

This step helps to separate objects in the image and identify them, often using algorithms such as K-means clustering or deep learning image segmentation techniques.

Step 4: Feature Extraction

Machine Vision will extract features of objects in the image such as color, shape or other elements to distinguish between different objects.

Step 5: Object Classification

Based on the extracted features, classification algorithms help Machine Vision recognize and classify objects into different groups.

Step 6: Synthesize results

Finally, the system synthesizes the analysis results, provides quality assessment, detects errors or supports robot control.

The role of light in Machine Vision

Light is an important factor that determines image quality in Machine Vision, directly affecting the clarity and reliability of the captured image. To achieve high-quality images, light must be adjusted to suit each specific application.

Common types of light in Machine Vision:
Uniform light: Ensures consistent brightness across the entire image acquisition area, increasing accuracy.

Angle light: Creates high contrast, highlighting small details in the image.

Reflected light: Increases the brightness inside the object, improving contrast and image detail.

Laser light: Creates clear dark and bright areas, good support for analyzing complex surfaces.

Infrared light: Suitable for observing surfaces that are difficult to detect with conventional light.

When choosing a lighting system for Machine Vision, manufacturers need to ensure that the light is suitable for specific application requirements, thereby achieving optimal efficiency in the production process.

Benefits of Machine Vision in Manufacturing

Machine vision in manufacturing significantly improves efficiency and product quality, with a variety of uses suitable for each industry and manufacturing environment. Machine vision is used for finished product quality inspection, label verification, defect inspection, code verification, orientation inspection, traceability, packaging inspection, barcode reading, and more. Here are 10 common applications of machine vision in manufacturing:

Predictive maintenance

Robot-mounted cameras collect images and send them to a processing center for analysis, helping to detect and handle potential problems before they cause problems.

Packaging defect inspection

Images are captured and analyzed to check factors such as color, size, packaging width, helping to eliminate unsatisfactory products.

Barcode reading

Manual barcode reading is time-consuming and error-prone. Machine vision automates this process, reducing errors and optimizing production costs.

Assembly Component Monitoring

With 360-degree inspection capabilities, machine vision ensures products are assembled correctly and checks attributes such as lid closure, print quality, and labels.

Defect Detection

Ensures products meet standards and are free of defects before leaving the factory.

3D Inspection

Machine vision uses high-resolution images to create 3D models, helping to identify small errors in the circuit structure, ensuring that the production line is not interrupted.

Improves Workplace Safety

Machine vision can track movements and predict dangerous interactions between humans and equipment, helping to minimize the risk of accidents.

Track & Trace

Supports controlling the transportation status of goods at each point in time.

Text Analysis

Machine vision can analyze text on packaging, labels or products to ensure accuracy.

Artificial Intelligence (AI) Development Platform

Machine vision provides data and images to support AI applications, helping to optimize the entire production process.

Intech Group is a leading provider of comprehensive automation solutions, including machine vision applications in manufacturing. This solution helps businesses improve product quality, increase productivity and profits, and contribute to promoting automation in product inspection and classification.

Applications of Machine Vision in Industry 4.0

Supported by Industrial Cameras, machine vision systems can measure and count products, calculate their weight or volume. In addition, machine vision can inspect goods at the highest speed with pre-defined characteristics. Besides, they automatically extract important information from huge data or help experts interpret images by selecting, optimizing and supplementing images.

In addition, this technology is also applied as follows:

Object recognition: Machine Vision can detect, recognize and classify objects in images or videos. From basic objects such as straight lines, squares to complex objects such as industrial products.

Measurement and quality inspection: Machine Vision can measure the size, shape, position and other parameters of objects to check quality and ensure compliance with quality standards.

Fault Detection: Machine Vision can detect faults in the manufacturing process or physical devices. From basic faults such as chips, scratches to more complex faults such as differences in color and shape.

Tracking and monitoring: Machine Vision can monitor and track objects, manufacturing processes. At the same time, alert users to unwanted events.

Automation: Machine Vision can automate the manufacturing and measurement process to minimize human intervention, increase productivity and ensure accuracy in production.

Devices in machine vision systems

Machine Vision systems include many important devices to support the automation of inspection, measurement and analysis of image data in production. Here are the basic devices and their roles:

1. Camera

Cameras are the key devices in machine vision systems, used to collect images of objects to be inspected. There are many types of cameras used in machine vision, including:

• Standard cameras: Provide options for resolution and number of pixels to suit each application.

• Smart cameras: Integrated microprocessors to process images directly without connecting to a computer.

• 3D cameras: Provide the ability to scan and analyze three-dimensional images, helping to increase accuracy in product inspection.

• Thermal cameras: Used to check and monitor temperature factors in production environments, especially useful in industries such as electronics and automobiles.

2. Software

Software is an essential element in a machine vision system, helping to process and display image data from the camera. Software in machine vision has the following main features:

• Data visualization: Displays images captured by the camera, making it easy for operators to analyze and maintain the system.

• Hardware programming and control: Allows configuration and adjustment of system functions such as lighting, camera modes, and image processing algorithms.

• Off-the-shelf software: Provides options to suit specific system requirements, helping to optimize efficiency and reliability in image analysis.

3. Other Devices

In addition to cameras and software, machine vision systems also need other supporting devices such as:

• Embedded systems: Microprocessors or integrated circuits to process data right at the image collection site.

• Frames and brackets: To fix the system components, ensure the captured images are stable and accurate.

• Lighting: Create suitable lighting conditions, improve image quality.

• Lens: Helps adjust the camera's viewing angle and magnification.

• Computer: Handles complex analysis algorithms if the system does not have a smart camera.

• Connection cables: Ensure data from the camera is transmitted to the computer or processing device.

• Label verification equipment and robots: Integrated to accurately check and verify product labels and control operations in the production line.

With these devices, the machine vision system can meet diverse automation needs, optimize production processes and ensure product quality.

Intech Group provides specialized equipment and solutions for Machine Vision, automatic cargo transportation systems with conveyor systems, conveyor belts, AGV self-propelled vehicles, and automatic packaging machines. These products and services help businesses optimize time, save costs, reduce labor and improve product quality comprehensively.

See more: What is automation equipment?