MACHINE VISION

1. Introduction to Machine Vision

Machine Vision is a field of study within Artificial Intelligence (AI) that focuses on simulating the ability to see and understand the surrounding world on a computer. It involves the acquisition, processing, and analysis of images and videos to extract useful information.

Machine Vision is a promising research and application field that plays a key role in driving the development of AI and automation. With the continuous advancement of technology, Machine Vision is expected to bring many benefits to humans in the future.

The history of Machine Vision development can be divided into three main stages:

• Stage 1 (1960 - 1970): This stage focused on developing basic image processing algorithms such as image filtering, image segmentation, and feature recognition.

• Stage 2 (1980 - 1990): This period saw the emergence of more advanced Machine Vision algorithms, based on statistical models and machine learning.

• Stage 3 (2000 - present): Marked by the explosion of deep learning, particularly Convolutional Neural Networks (CNNs), this stage has taken Machine Vision to a new level, enabling computers to solve more complex vision problems more efficiently.

2. Key Components of Machine Vision

Machine vision plays a crucial role in product quality control, automating production processes, and enhancing operational efficiency. Below are the key components of machine vision:

2.1 Industrial Computer
The Industrial Computer is responsible for processing the image data received from the camera and performing machine vision algorithms. The Industrial Computer integrates multiple ports for communication with peripheral devices. Specialized software is installed on this computer to execute image processing algorithms and control the system.

2.2 Frame Grabber Card
The Frame Grabber Card serves as the interface between the camera and the industrial computer. It is responsible for converting the analog image signal from the camera into a digital signal that the computer can process. The Frame Grabber Card needs to have a high capture rate, high resolution, and support various camera standards.

2.3 Camera
The camera is the component that captures images or videos of products or objects in the industrial environment. The quality of the images captured by the camera directly affects the accuracy of the processing and analysis process. Important camera factors include resolution, capture speed, and the ability to function in various lighting conditions.

2.4 Lighting (Lighting System)
The lighting system provides the necessary illumination for the camera to capture clear and accurate images. The lighting system must be designed to suit the working environment conditions and the characteristics of the product being inspected.

3. Machine Vision Technologies
   Machine vision systems use artificial intelligence (AI) to simulate the ability to recognize and classify objects similar to humans. To train computers to recognize image data, computer scientists provide them with large amounts of information. The machine vision technologies include:

3.1 Deep Learning
Deep learning is a subfield of artificial intelligence that uses artificial neural networks to analyze and learn from image data. These neural networks consist of layers of software modules called artificial neurons, which work together inside the computer. They use mathematical computations to automatically process various aspects of image data and gradually build a combined understanding of the image. This process allows the computer to recognize and classify objects with high accuracy.

3.2 Convolutional Neural Networks (CNN)
Convolutional neural networks (CNN) are a specialized type of neural network widely used in image data analysis. They use a labeling system to classify image data and understand the whole image. CNN analyzes images as pixel data and assigns a label value to each pixel. This value is then used to perform a mathematical operation called convolution to make predictions about the image. CNN starts by identifying simple shapes and outlines before refining more complex details, allowing it to accurately and efficiently recognize objects in images.

3.3 Recurrent Neural Networks (RNN)
Recurrent neural networks (RNN) are another type of neural network, but they have the ability to process a series of images to find connections between them. While CNN is used for analyzing individual images, RNN can analyze videos and understand the relationships between images over time.

4. Applications of Machine Vision
Machine vision is an advanced technology with high applicability across various industrial sectors. Below are the main applications of machine vision:

4.1 Quality Control
Machine vision systems are capable of detecting and eliminating products that do not meet quality standards, such as those that are damaged, incorrectly sized, discolored, or improperly positioned. This helps to:

• Ensure the final product meets high-quality standards.
• Minimize error rates and reduce product waste.
• Enhance the reliability and reputation of the product in the market.

4.2 Automation Capability
Machine vision plays an essential role in enhancing the automation of manufacturing processes. With its ability to quickly identify and analyze, machine vision systems help:

• Increase production efficiency by reducing inspection and product processing time.
• Optimize the manufacturing process by automatically adjusting parameters and workflows.
• Reduce dependency on manual labor and minimize human error.

4.3 Information Control
Machine vision is also used for identifying and controlling information on products. The system can read and identify details such as barcodes, data codes, date codes, and other printed characters on products. These applications help to:

• Ensure the accuracy and traceability of product information.
• Automate the verification and inspection of product information.
• Improve inventory and logistics management.

4.4 Cost Optimization
Using machine vision in production lines helps reduce costs by automating processes and reducing human intervention. The system provides numerous benefits, such as:

• Lower labor and training costs.
• Increased production efficiency and reduced downtime.
• Enhanced material usage efficiency and reduced waste.

5. Applications of Machine Vision
Machine vision is an advanced technology with broad applicability in various fields. Below are some prominent applications of machine vision:

5.1 Applications in Pharmaceuticals

• Combining machine vision in the pharmaceutical industry.
• Inspecting the appearance and quality of products (e.g., broken, cracked, chipped, mislabeling, color differences, etc.).
• Controlling product quantity (e.g., number of pills, number of blister packs, bottles of medicine, etc.).

5.2 Applications in Food Industry

• Machine vision is used to monitor the quality of printed information such as production date, expiration date, batch number, shift details, etc.
• It can also be integrated with software to manage quantities and send production parameters.

5.3 Applications in Component Manufacturing

• Inspecting the appearance of components (e.g., measuring dimensions, position and orientation of components, detecting dents, defects, etc.) to ensure quality for production input.

5.4 Applications in Straw Inspection

• Checking the accuracy of straw placement.
• Detecting misaligned straws.
• Identifying packages without straws.

5.5 Applications in Label Inspection

• Checking the position of labels (e.g., misalignment, peeling off).
• Inspecting label content (e.g., missing or extra text, peeling off).
• Detecting products without labels.

6. Providers of Machine Vision Solutions

In the context of modern industry, machine vision has become an essential technology that helps businesses enhance product quality, optimize production processes, and reduce costs. I&C is proud to be one of the leading providers of machine vision solutions. Highlights of I&C include:

• Highly specialized engineering team: I&C boasts a team of highly skilled engineers with deep knowledge in machine vision and extensive practical experience in implementing projects.

• Strong research and development capabilities: I&C continuously invests in research and development, always updating with the latest machine vision technologies to provide optimal solutions for customers.

• Effective consulting and implementation capabilities: I&C offers professional consulting services, helping clients identify their needs and select appropriate solutions. I&C also ensures effective project implementation, ensuring stable system operation and meeting customer requirements.

• Competitive pricing: I&C provides machine vision solutions at competitive prices, suitable for the budgets of many businesses.

• Attractive promotion policies: I&C regularly offers special promotions to help clients save costs when investing in machine vision solutions.

If you are looking for an efficient and reliable machine vision solution, contact I&C today. We are ready to listen to your needs and provide the best solutions. For more information and free consultation, please contact us at:

I&C ENGINEERING SERVICE CO., LTD
Address: 54, Street 182, Tăng Nhơn Phú A Ward, Thủ Đức City, Ho Chi Minh City
Phone: 0982 805 485
Email: sales@ices.com.vn
Website: ices.com.vn