Computer vision, a sector in automation and computer science, allows for imitating human vision and acts upon the factor of perception based on received images. Computer vision and artificial intelligence are highly intertwined. This branch incorporates AI to process images and videos and is used in controlling industrial automation processes, self-driving vehicles, detecting anomalies and flaws, predicting events, medical image analysis, etc. Advancements in AI is directly proportional to technical upgradations in computer vision technology.
But AI is not the only factor that effects computer vision. Economics suggests, increase in demand fuels an increase in technological prowess. Such is the case regarding computer vision where the market plays a key role in its growth.
Computer vision has witnessed rampant commercialization in the past decade and is being deployed in a wide array of industries. Not surprisingly, these were just design concepts a few years ago but market demand finally caught up and had the stream on a full swing. We can attribute such rapid global adoption of machine vision to the following factors:
The x-factor of the computer vision system is its ability to process large amounts of graphical information in just a fraction of time. This is equivalent to two dozen humans tirelessly running every bit of information. This quick processing ability is what drives computer vision into some of the major sectors in the world. Especially in the manufacturing sector, computer vision has helped it reach new milestones and set benchmarks by producing defects of fewer products.
Moreover, as more and more industries embrace robots, there has been a rise in the usage of computer vision in such robotic systems, thereby dishing out vision-guided robotic systems. As fields such as automotive, pharmaceutical, and food-beverage are key users of the robotic system, they are also fuelling demand for machine vision solutions.
Depending on varied requirements regarding quality and safety, a computer vision system incorporates various hardware accessories to capture images, clips, and analyze them. These along with the AI and deep learning technology lends operational control to devices that capture and process images and execute specific functions as required for decision making. Some key hardware components include, if not limited to smart cameras, image sensors, lighting, vision processing, and communication devices.
According to leading market research reports:
Here is how machine vision is increasingly finding its presence in different fields:
The computer vision technology genre continues to experience frequent and relentless transformation, all the while paving way for new technology upgrades. The integration of deep learning and AI with CV solutions has remarkably increased the level of effectiveness of the technology. No wonder computer vision has quickly seen itself in every other industry vertical. Smart computer vision is regarded as a high potential technology worth investing upon, and judging by the current scenario, the future looks bright.
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