As per the market research’s prediction, the global machine vision market is set to witness growth with a CAGR of 7.49% over the forecasting years of 2019-2027.

A machine vision system incorporates the technology that allows a computer to identify and inspect images. It has similar applications to voice recognition technology, but makes use of images instead. Machine vision systems enable to extract data from digital images which helps manufacturers to reduce costs, enhance quality and streamline their overall processes. MV systems are primarily used for repetitive tasks like inspection and gauging. With the help of machine vision systems, these tasks have become cost-effective and increasingly easy to implement.

Technology needs to evolve with the progression of time and the need for automated inspection and monitoring have given rise to the market for machine vision. Machine vision systems not only help in automated inspection processes, but also for detecting defects, monitoring processes, quality assurance, factory floor management and packaging warehouse monitoring. Additionally, human workers are not able to perform tasks with accuracy and precision at all times, thus making MV systems a lucrative option.

The rise in the need for smart factories, increasing need for proper defect detection, the ever-expanding applications of machine vision systems and trends such as miniaturized products are factors driving the growth of this market. The utilization of image sensors in machine vision systems aids to system miniaturization, high-speed imaging and avoid blooming & smearing effects, which is a typical disadvantage of charged couple devices (CCD).CMOS image sensors replace CCD technology in cameras of machine vision systems as they offer numerous advantages, such as lower voltage operation, lower cost, lower power consumption, and on-chip functionality. Thus, the constant development of CMOS image sensors provides growth opportunities to the machine vision market.

However, despite the several business benefits offered by machine vision, it still remains to be utilized to its optimal potential, which is because of the lack of expertise in operating these systems. Successful post-implementation functioning of MV systems require a high amount of proficiency, a skill that many professionals lack. Furthermore, some of the companies opting for this technology find it difficult to operate them due to insufficient knowledge of the system. This need for ease of use and reduced difficulty in operating MV products is proving to be a challenge for the machine vision product vendors.

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