【Introduction】With the ever-changing production goals and the increasingly tight fulfillment time, manufacturing and logistics companies have also undergone tremendous changes in recent years, and there is an urgent need to simplify processes and adopt new technologies to meet customer habits and expectations. change. Manufacturers and supply chains need a certain level of flexibility to adjust individual workflows and overall operations faster, and machine vision and computer vision are two things that can help the manufacturing and logistics industries achieve greater efficiency. and flexible technology.
Difference Between Machine Vision and Computer Vision
Machine vision and computer vision sound similar. To some extent, they are indeed similar, both techniques are used to acquire and analyze images. But the design goals of the two are quite different. To gain a better understanding of machine vision and computer vision techniques, it is easier to understand by starting with the similarities.
Both technologies are intelligence-based systems that can be used to acquire, process and analyze images. In both enterprise and industrial settings, machine vision and computer vision solutions can help improve quality and process control by capturing individual problems and patterns that employees may overlook.
For example, spot inconsistencies in business operations processes and adopt systems that notify key employees of anomalies and help them develop relatively effective courses of action. In addition, it can also help businesses avoid major losses in inventory, finances or customers.
The difference between machine vision and computer vision is the speed and level of information collection, distribution and application.
Empowering manufacturing and logistics companies to improve efficiency
Machine vision solutions are often self-contained and have on-premises capabilities to capture images and process data. This technology is ideal for production lines. On the production line, manufacturers need to be able to spot visual inconsistencies in labels, packaging or product designs simply and quickly.
Businesses can also place smart cameras in stationary industrial scanners above warehouse conveyor belts to analyze items passing through the conveyor belt. This can be used to analyze barcodes, analyze data through integrated sensors, and inform operators of various anomalies about the contents of the package or destination before the shipment is sent to the customer, thereby increasing the efficiency and speed of the product line operation, and Bugs are also easier to spot. This saves costs and helps warehouse managers focus on other operational tasks.
Computer vision takes a different approach, using advanced algorithms to conduct a more comprehensive analysis. Similar to machine vision, it can help decision makers understand their own operations. But computer vision can “see further,” helping key stakeholders understand why events happen. This technology is more suitable for use in retail, healthcare and other industries along with other enterprise-level intelligent solutions.
Because computer vision needs to analyze more data, it usually takes longer than machine vision to provide the information needed for decision-making, and its qualitative analysis is more suitable for including intelligent automation solutions, biopsy scanners and mobile computers, etc. first-line image acquisition technology.
Companies are already using computer vision to help simplify the shopping process. For example, retailers can use cameras and computer vision technology to track items that customers take away. Such technology can also add various items to a virtual shopping basket and automatically check out after a customer leaves the store, without the laborious scanning of items using traditional point-of-sale technology and the need for customers to wait in line to pay.
The impact of industrial automation technology on the overall supply chain
Machine vision and stationary industrial scanners are not only having an impact on the manufacturing industry, but are also causing significant changes in the overall supply chain. Warehouse and distribution center operators have been looking for ways to simplify the returns process, and this has become more apparent in recent years.
Industrial automation technologies, such as Zebra’s dual-function machine vision and stationary industrial scanning solutions, can take on some of the heavy lifting and help companies automate the collection, analysis and application of various data in an easier way. For example, cameras can verify the quality of returned items before refunds are issued to customers and goods are put back on shelves, while barcode readers can automatically record returned items in an inventory management system. This helps retailers move inventory more quickly and sell again.
Collectively, machine vision and computer vision can be applied across multiple supply link touchpoints to help manufacturing and logistics efficiently respond to customers’ changing needs and ensure retailers have quality merchandise that provides an exceptional customer experience.
Source: Cheng Ning, Technical Director of Zebra Technology Greater China
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