Machine vision or MV is a method or technology which is used to deliver imaging-based automatic analysis and inspection for applications such as process control, robot guidance, and automatic inspection. Machine vision is a term that includes a variety of technologies, hardware and software products, actions, and integrated systems. Machine vision can be considered different from computer vision. Machine visions are primarily of two types – 2D (two dimensional) and 3D (three dimensional). The usage of 2D or 3D machine vision systems depends upon the application they are used in.
In 2D machine vision, a 2D map (X, Y) of the reflected intensity is taken and then it is processed. The processing usually consists of comparing contrasts (variations in intensity). 2D machine visions are conventionally used for applications such as label orientation, barcode reading and printing verification. On the contrary, 3D machine vision systems deals with all the three axes (X, Y, and Z). 3D Machine Vision scanners gives a point cloud (three dimensional coordinates) output. It is a digitized model of location and shape of object(s) scanned. Additionally, 3D machine vision has the ability to combine various point clouds from several scanners. For instance, a large entities such as a truck frame are scanned with multiple scanners if the scanners are placed strategically. Constant change in consumer requirement may pose a threat to the growth of the market. However, the enhanced functionalities of 3D machine vision systems are likely to drive the overall 3D Machine Vision market.
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The global Machine Vision market can be segmented on the basis of product type, offerings, application, and geography. By product type, the market can be divided into pc-based systems and smart camera-based systems. Camera based systems are likely to grow at a maximum rate in the coming years. Cameras are the eyes of machine vision systems; they constitute sensors that can transform light in the lens into electrical signals. With the advancement of digitalization, 3D machine vision cameras have additional features such as high storage capabilities, built-in processing units and high-quality imaging. The global demand for image processing, compactness, and high-quality images has been increasing at a steady rate, thereby encouraging the growth of the 3D Machine Vision market during the forecast period.
By the type of offerings the global 3D Machine Vision market can be segregated into hardware and software. The hardware segment held a significant share of the global market in the coming years owing to technological advancements in the field of 3D cameras and image detection techniques. On the basis of application, the market can be classified into quality assurance & inspection, positioning & guidance, measurement, identification, and others. High instances of theft as well as increasing demand for global positioning systems will impact the positioning and guidance segment positively. This in turn will drive the global 3D Machine Vision market.
In terms of geography, the global 3D Machine Vision market can be segmented into North America, Europe, Asia Pacific, Latin America, and Middle East and Africa. Asia Pacific held the maximum share of the global 3D Machine Vision market in 2016. The market in this region is anticipated to grow at a considerable rate between 2017 and 2025. Rising adoption of automation across all industry verticals, especially in automotive and consumer electronics, is one of the prime reasons for the growth of the market in this region. Moreover, existence of key manufacturing companies in countries such as Japan, China, and South Korea will boost the growth of the 3D Machine Vision market in the Asia Pacific region.
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The key players operating in the global 3D Machine Vision Market are Cognex Corporation (U.S.), National Instruments Corporation (U.S.), Keyence Corporation (Japan), Isra Vision AG (Germany), Sick AG (Germany), Basler AG (Germany), Mvtec Software GmbH (Germany), LMI Technologies (Canada), Stemmer Imaging (U.K.), and Tordivel As (Norway).
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