Mechatronics (Part-III)- Machine Vision In Automatic Inspection

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Find Out In Details About The Role Of Machine Vision In Automatic Inspection

Now we continue with the third part of our blog on mechatronics. Those who have missed our second blog can read it from Here. It will help to connect with the third part of the blog discussing about the role of machine vision in automatic inspection. Let us explore the blog to find these out in more details.

Machine vision (MV) is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision is a term encompassing a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science. It attempts to integrate existing technologies in new ways and apply them to solve real world problems. The term is also used in a broader sense by trade shows and trade groups; this broader definition also encompasses products and applications most often associated with image processing. Definitions of the term "Machine vision" vary, but all include the technology and methods used to extract information from an image, as opposed to image processing, where the output is another image. The information extracted can be a simple good-part/bad-part signal, or more a complex set of data such as the identity, position and orientation of each object in an image. The information can be used for such applications as automatic inspection, damage quantification and robot and process guidance in industry, or for security monitoring. This field encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of basic computer science; machine vision attempts to integrate existing technologies in new ways and apply them to solve real world problems in a way that meets the requirements of industrial automation and similar application areas.The term is also used in a broader sense by trade shows and trade groups such as the Automated Imaging Association and the European Machine Vision Association. This broader definition also encompasses products and applications most often associated with image processing.The primary uses for machine vision are automatic inspection and industrial robot/process guidance.

Imaging Based Automatic Inspection, Sorting and Damage Quantification

The primary uses for machine vision are imaging-based automatic inspection and sorting and robot guidance; in this section the former is abbreviated as "automatic inspection". The overall process includes planning the details of the requirements and project, and then creating a solution.A number of previous studies have also focused on machine vision applications in infrastructure contexts to estimate damage and load states. 

Methods and Sequence of Operation

The first step in the automatic inspection sequence of operation is acquisition of an image, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing. MV software packages and programs developed in them then employ various digital image processing techniques to extract the required information, and often make decisions (such as pass/fail) based on the extracted information.

Equipment

The components of an automatic inspection system usually include lighting, a camera or other imager, a processor, software, and output devices. The imaging device (e.g. camera) can either be separate from the main image processing unit or combined with it in which case the combination is generally called a smart camera or smart sensor. When separated, the connection may be made to specialized intermediate hardware, a custom processing appliance, or a frame grabber within a computer using either an analog or standardized digital interface (Camera Link, CoaXPress). MV implementations also use digital cameras capable of direct connections (without a framegrabber) to a computer via FireWire, USB or Gigabit Ethernet interfaces.

Imaging

While conventional (2D visible light) imaging is most commonly used in MV, alternatives include multispectral imaging, hyperspectral imaging, imaging various infrared bands, line scan imaging, 3D imaging of surfaces and X-ray imaging. Key divisions within MV 2D visible light imaging are monochromatic vs. color, resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes. Though the vast majority of machine vision applications are solved using two-dimensional imaging, machine vision applications utilizing 3D imaging are a growing niche within the industry. The most commonly used method for 3D imaging is scanning based triangulation which utilizes motion of the product or image during the imaging process. A laser is projected onto the surfaces of an object and viewed from a different angle. In machine vision this is accomplished with a scanning motion, either by moving the workpiece, or by moving the camera & laser imaging system. The line is viewed by a camera from a different angle; the deviation of the line represents shape variations. Lines from multiple scans are assembled into a depth map or point cloud.Stereoscopic vision is used in special cases involving unique features present in both views of a pair of cameras. Other 3D methods used for machine vision are time of flight and grid based. One method is grid array based systems using pseudorandom structured light system as employed by the Microsoft Kinect system circa 2012.

Continued in the next blog...