Difference between machine vision and computer vision

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Difference between machine vision and computer vision

June 10 , 2023 0

With ever-changing production targets and increasingly tight production times, manufacturing and logistics companies have also undergone tremendous changes in recent years. In order to meet customer habits and expectations, there is an urgent need to streamline processes and adopt new technologies. Manufacturers and supply chains need some flexibility to adjust individual workflows and overall operations more quickly, and machine vision and computer vision are two technologies that can help the manufacturing and logistics industries achieve greater efficiency and flexibility.

Difference between machine vision and computer vision

Machine vision and computer vision sound very similar. In a way, they are similar. Both techniques are used for image collection and analysis. But they are designed for very different purposes. In order to better understand machine vision and computer vision technology, it is easier to understand from the similarities.

Both technologies are based on intelligent systems that can be used for image collection, processing, and analysis. In corporate and industrial environments, machine vision and computer vision solutions can help improve quality control and process control by capturing individual issues and patterns that employees may miss.

For example, finding inconsistencies in business operations and using systems that notify key employees of anomalies helps them develop relatively effective action plans. In addition, it can help businesses avoid major losses in inventory, finance, or customers.

Machine vision differs from computer vision in the speed and level of information collection, distribution, and application.

Enable manufacturing and logistics companies to improve efficiency

Machine vision solutions are typically self-contained, with locally deployed image collection and data processing capabilities. This technology is ideal for production lines. On the production line, manufacturers need to be able to visually easily and quickly spot inconsistencies in labels, packaging, or product design.

Businesses can also place smart cameras in stationary industrial scanners above warehouse conveyor belts to analyze various items through them. This can be used to analyze barcodes, analyze data through integrated sensors, and tell operators of various anomalies in the project or destination package before it is sent to the customer, to improve the efficiency and speed of the product line, and errors are more easily detected. This saves costs and helps warehouse managers focus on other operations.

Computer vision takes a different approach. The technology uses advanced algorithms for more comprehensive analysis. Similar to machine vision, it helps decision makers understand their actions. But computer vision can "see further" and it can help key stakeholders understand the causes of various events. The technology is more suitable for other enterprise-class intelligent solutions in retail, healthcare and other industries.
Because computer vision needs to analyze more data, it usually takes longer than machine vision to provide the information needed to make decisions. Its qualitative analysis is more suitable for first-line image acquisition technologies, including intelligent automation solutions, biopsy scanners and mobile data terminals.

Currently, businesses use computer vision to help streamline the shopping process. For example, retailers can use cameras and computer vision technology to track what customers take away. This technology can also add a variety of items to a virtual shopping basket and automatically settle after the customer leaves the store, without using traditional point-of-sale technology to scan the items and customers need not queue up to pay.

The impact of industrial automation technology on the entire supply chain

Machine vision and fixed industrial scanners are not only having an impact on manufacturing, but are also undergoing dramatic changes throughout the supply chain. This has become even more apparent in recent years as warehouse and distribution center operators have been looking for ways to streamline the return process.

Industrial automation technologies, such as machine vision and fixed industrial scanning solutions with dual-function Zebra Technology, can take on some of the heavy lifting tasks and help enterprises achieve automatic collection, analysis and application of various data in a simpler way. For example, cameras can verify the quality of returns before refunds are made to customers and goods are restocked, while barcode readers can automatically record returns in inventory management systems. This helps retailers move inventory more quickly and sell again.

In general, machine vision and computer vision can be applied to multiple supply chain touchpoints, helping the manufacturing and logistics industries effectively respond to changing customer needs and ensuring retailers have high-quality products that deliver an excellent customer experience.