A recent report by ABI Research indicates that total shipments for machine vision sensors and cameras will reach 16.9 million by 2025, creating an installation base of 94 million machine vision systems in industrial manufacturing—11 percent of which will be deep-learning based. The report, Machine Vision in Industrial Applications, outlines the importance of machine vision technology, which is a central factor in the global push toward greater automation.
Machine vision systems are often utilized in production lines for barcode reading, quality control and inventory management, but have recently found a demand in other areas as well.
“Robotics, for example, is a new growth area for machine vision: collaborative robots rely on machine vision for guidance and object classification, while mobile robots rely on machine vision for SLAM and safety,” stated Lian Jye Su, Principal Analyst at ABI Research.
On the other hand, deep learning-based machine vision systems are data-driven and make use of a statistical approach, which allows the machine vision model to improve as more data is gathered for training and testing.
Companies around the world are learning to implement machine vision tech into their product lines in order to better specialize their designs and increase overall efficiency. Lattice Semiconductor, for instance, is focusing on low-powered AI for embedded vision, while Intel is deploying pre-trained deep learning-based machine vision models through a common API.
Su concludes, “When choosing machine vision systems, end implementers need to understand their machine vision requirements, consider integration with their backend system, and identify the right ecosystem partners. Deployment flexibility and future upgradability and scalability will be crucial as machine vision technology continues to evolve and improve.”
You can purchase the full ABI Research report here.