Machine vision (MV) is the technology and techniques utilized to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, hardware and software 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 word is the prevalent one for these functions in industrial automation environments but can also be used for these functions in other environments such as security and vehicle guidance.
The general Top Machine Vision Inspection System Manufacturer includes planning the facts of the requirements and project, and after that creating a solution. During run-time, the process starts with imaging, followed by automated research into the image and extraction from the required information.
Definitions from the term “Machine vision” vary, but all range from the technology and techniques used to extract information from a picture upon an automated basis, as opposed to image processing, where the output is an additional image. The data extracted can become a simple good-part/bad-part signal, or even more a complicated set of information like the identity, position and orientation of each and every object within an image. The information can be applied for such applications as automatic inspection and robot and process guidance in industry, for security monitoring and vehicle guidance. This industry encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision is virtually the only expression used for these functions in industrial automation applications; the term is less universal for such functions in other environments such as security and vehicle guidance. Machine vision being a systems engineering discipline can be considered distinct from computer vision, a type of basic computer science; machine vision efforts to integrate existing technologies in new ways and apply them to solve real world problems in a manner in which meets the prerequisites 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 as well as the European Machine Vision Association. This broader definition also encompasses products and applications usually connected with image processing. The primary ways to use machine vision are automatic inspection and industrial robot/process guidance. See glossary of machine vision.
Imaging based automatic inspection and sorting
The main uses of machine vision are imaging-based automatic inspection and sorting and robot guidance.;:6-10 in this particular section the former is abbreviated as “automatic inspection”. The overall process includes planning the details of the requirements and project, and after that creating a solution. This section describes the technical procedure that occurs throughout the operation of the solution.
Methods and sequence of operation
Step one inside the automatic inspection sequence of operation is acquisition of your image, typically using cameras, lenses, and lighting that has been made to supply the differentiation required by subsequent processing. MV software applications and programs developed in them then employ various digital image processing techniques to extract the required information, and quite often make decisions (such as pass/fail) based on the extracted information.
The components of an automatic inspection system usually include lighting, a camera or some other imager, a processor, software, and output devices.3
The imaging device (e.g. camera) can either be apart from the key image processing unit or along with it where case the combination is normally called a smart camera or smart sensor When separated, the link may be produced to specialized intermediate hardware, a custom processing appliance, or perhaps a frame grabber in a computer using either an analog or standardized digital interface (Camera Link, CoaXPress) MV implementations also have digital camera models able to direct connections (without a framegrabber) to your computer via FireWire, USB or Gigabit Ethernet interfaces.
While conventional (2D visible light) imaging is most often found in MV, alternatives include multispectral imaging, hyperspectral imaging, imaging various infrared bands,line scan imaging, 3D imaging of surfaces and X-ray imaging. Key differentiations within MV 2D visible light imaging are monochromatic vs. color, frame rate, resolution, and whether or not the imaging process is simultaneous over the entire image, making it ideal for moving processes.
Though nearly all machine vision applications are solved using two-dimensional imaging, Automated Vision Inspection Machines utilizing 3D imaging certainly are a growing niche inside the industry. Probably the most widely used technique for 3D imaging is scanning based triangulation which utilizes motion of the product or image throughout the imaging process. A laser is projected onto the surfaces nefqnm an object and viewed from the different angle. In machine vision this is accomplished with a scanning motion, either by moving the workpiece, or by moving your camera & laser imaging system. The line is viewed with a camera from the different angle; the deviation of the line represents shape variations. Lines from multiple scans are assembled in to a depth map or point cloud. Stereoscopic vision is used in special cases involving unique features contained in both views of a couple of cameras. Other 3D methods employed for machine vision are duration of flight and grid based.One method is grid array based systems using pseudorandom structured light system as used by the Microsoft Kinect system circa 2012.