Five trends in the development of machine vision technology are briefly described

The past year has seen unprecedented developments in the fields of artificial intelligence (AI), big data, 3D imaging and robotic process automation. In the coming 2023, the application of machine vision technology will also flourish, the following Xinxiwang leads you to understand the five major trends in the development of machine vision technology:

1.3D imaging and Bin Picking

Industrial automation is driving factories to become more intelligent and can replace human labor to reduce labor. Machine vision for quality control inspection has been widely used, but with the advent of 3D sensors and integrated solutions for robotic picking, new markets are opening up. Regardless of the position and orientation of the part, the robot pickup system can pick up objects randomly. The 3D vision system can identify a large number of randomly placed parts, such as suitcases and parts boxes. Due to the robot's dynamic processing, complex objects can be selected in different orientations and stacks. Combining artificial intelligence (AI) with pick-up operations enables part self-selection, increasing productivity and cycle time, and reducing the need for human-machine interaction in the process.

2. Cloud deep learning

The arrival of 5G data networks provides autonomous vehicles with the ability to perform cloud-based machine vision calculations. Massive Machine Type Communication (mMTC) allows large amounts of data to be processed in the cloud for use in machine vision applications. Deep learning algorithms using convolutional neural network classifiers can quickly classify, detect and segment images. In the coming year, the development of these new AI and deep learning systems will increase.

3. Robots

According to the International Federation of Robotics, 2018 was a record year for robot sales, with sales of industrial robots increasing by 31%. Trends such as human collaborative robots, simplified use, and process learning have helped drive the use of robots in industrial automation. In the future, industrial robots will be easier and faster to program using intuitive interfaces. Man-machine collaboration will support small batch, high complexity of flexible production. The reduction in the complexity of use allows robots and vision systems to be widely used in the medium to long term.

4. Hyperspectral imaging

Next generation modular hyperspectral imaging systems provide performance analysis of chemical materials in industrial environments. Chemical color imaging visualizes the molecular structure of a material through the resulting images of different colors. This allows the chemical composition to be analyzed in standard machine vision software. Typical applications include plastic inspection in meat production, inspection of different recyclable materials, and quality control for pellet inspection. The main obstacles to such systems are the amount and speed of data needed to process them, but the development of faster processing, better algorithms and camera calibration still make them a hot topic in 2019.

5. Thermal imaging industrial detection

Thermal imaging cameras have traditionally been used for defense, security and public safety, and thermal imaging technology is widely used for detection. For many industrial applications, such as parts production for the automotive or electronics industries, thermal data is critical. While machine vision can see production problems, it cannot detect thermal anomalies. Thermal imaging combined with machine vision is a growing field, which allows manufacturers to spot problems that cannot be seen by the naked eye or standard camera systems. Thermal imaging technology provides non-contact precision temperature measurement and non-destructive testing, which is the direction of development in the field of machine vision and automated control.

Sum up

Technologies associated with Industry 4.0 are driving more changes in manufacturing. Machine vision is applicable to all industries, but it is particularly important in high-specification, highly regulated industries such as food and beverage, pharmaceutical and medical device manufacturing. Companies are turning to factory automation technology for a variety of reasons, including improving production line efficiency, using resources more efficiently and increasing productivity. According to speculation, it is expected that the demand for machine vision-related technologies in various fields will continue to grow in 2023.

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