Computer Vision and Machine Vision Market to See 11.7% Annual Growth Through 2024

Industry Boosted by Faster Hardware

Machine Vision

Due to an expanding number of potential applications and improvements, such as faster hardware, computer vision and machine vision will see substantial growth through 2024, according to a report by BCC Research, “Computer Vision and Machine Vision in Everyday Life.”

The market expects to see a compound annual growth rate (CAGR) of 11.7% through 2024, when it could be worth $26.0 billion.

Major players in the market include: AccuSentryAmazon Web Services IncKeyence Corp and Vision and Control Systems LLC.

Research Highlights

  • Cameras, including smart cameras, as a segment of the global market for computer vision and machine vision in everyday life, should grow from 4.0 billion in 2019 to 7.4 billion in 2024, at a CAGR of 13.0%.
  • Optics, lighting and frame grabbers should grow from 4.3 billion in 2019 to 7.5 billion in 2024 at a CAGR of 11.9%.
  • By region, North America will see the highest growth, growing from $4.6 billion in 2019 to $8.2 billion in 2024 at a CAGR of 12.1%.

Read the full report here: https://www.bccresearch.com/market-research/instrumentation-and-sensors/computer-machine-vision-market-report.html

“Demand for MV systems has increased in all everyday life applications, including medical devices, packaging, automotive, printing and publishing, consumer goods, traffic management and toll collection,” writes analyst Srinivasa Rajaram. “Applications, such as automatic plate number recognition, traffic flow monitoring, traffic surveillance and other related applications are witnessing increased integration and utilization of MV systems. Customers’ sophisticated demands are additional factors that are having positive effects on the MV industry.”

The Utility of Machine Vision in Security

MV serves security systems to detect unauthorized presence of people and objects, as well as to identify known criminals in various sensitive locations, the report adds. This is done by comparing camera images with photographic databases. In each case, human operators — not machines — make the final judgment before further action is taken. Images from closed circuit television (CCTV) cameras are routinely used in security systems despite being of poor quality and laborious to interpret. Two-dimensional and three-dimensional MV provides methods to enhance picture quality, interpret events and monitor complex scenes. Example applications include plate number identification, people tracking, face recognition and intruder monitoring.

Editors/reporters requesting analyst interviews should contact Sarah Greenberg at press@bccresearch.com.

Source: BCC Research


Categories: High Technology

Tags: AI, artificial intelligence, computer vision, machine learning, machine vision, MV, security


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Sarah Greenberg
Senior Content Strategist, BCC Research
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