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Machine vision

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Machine vision is the technology and methods used to provide <a href="Image" title="Image">imaging</a>-based <a href="Automation" title="Automation">automatic</a> inspection and analysis for such applications as automatic inspection, <a href="Process_control" class="mw-redirect" title="Process control">process control</a>, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise. Machine vision as a <a href="Systems_engineering" title="Systems engineering">systems engineering</a> discipline can be considered distinct from <a href="Computer_vision" title="Computer vision">computer vision</a>, a form of <a href="Computer_science" title="Computer science">computer science</a>. It attempts to integrate existing technologies in new ways and apply them to solve real world problems. The term is the prevalent one for these functions in industrial automation environments but is also used for these functions in other environment vehicle guidance.

The overall machine vision process includes planning the details of the requirements and project, and then creating a solution. During run-time, the process starts with imaging, followed by automated <a href="Image_analysis" title="Image analysis">analysis</a> of the image and extraction of the required information.

<div class="mw-heading mw-heading2"><h2 id="Definition">Definition</h2></div>

Definitions of the term "Machine vision" vary, but all include the technology and methods used to extract information from an image on an automated basis, as opposed to <a href="Image_processing" class="mw-redirect" title="Image processing">image processing</a>, 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 and robot and process guidance in industry, for security monitoring and vehicle guidance.<a href="#cite_note-TextbookP1-1">[1]</a><a href="#cite_note-Beyerer2016-2">[2]</a><a href="#cite_note-Gravespg5-3">[3]</a> This field encompasses a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise.<a href="#cite_note-Gravespg5-3">[3]</a><a href="#cite_note-Holton-4">[4]</a> Machine vision is practically the only term used for these functions in industrial automation applications; the term is less universal for these functions in other environments such as security and vehicle guidance. Machine vision as a <a href="Systems_engineering" title="Systems engineering">systems engineering</a> discipline can be considered distinct from <a href="Computer_vision" title="Computer vision">computer vision</a>, a form of basic <a href="Computer_science" title="Computer science">computer science</a>; 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.<a href="#cite_note-Gravespg5-3">[3]</a>: 5 <a href="#cite_note-5">[5]</a> 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.<a href="#cite_note-Holton-4">[4]</a> The primary uses for machine vision are automatic inspection and <a href="Industrial_robot" title="Industrial robot">industrial robot</a>/process guidance.<a href="#cite_note-NASAarticle-6">[6]</a><a href="#cite_note-AssemblyIntro2016-7">[7]</a>: 6–10 <a href="#cite_note-8">[8]</a> In more recent times the terms computer vision and machine vision have converged to a greater degree.<a href="#cite_note-davies5-9">[9]</a>: 13 See <a href="Glossary_of_machine_vision" title="Glossary of machine vision">glossary of machine vision</a>.

<div class="mw-heading mw-heading2"><h2 id="Imaging_based_automatic_inspection_and_sorting">Imaging based automatic inspection and sorting</h2></div>

The primary uses for machine vision are imaging-based automatic inspection and sorting and robot guidance.;<a href="#cite_note-NASAarticle-6">[6]</a><a href="#cite_note-AssemblyIntro2016-7">[7]</a>: 6–10 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 href="#cite_note-WestRoadmap-10">[10]</a><a href="#cite_note-IntegrationVandSJan2009-11">[11]</a> This section describes the technical process that occurs during the operation of the solution.

<div class="mw-heading mw-heading3"><h3 id="Methods_and_sequence_of_operation">Methods and sequence of operation</h3></div>

The first step in the automatic inspection sequence of operation is <a href="Digital_imaging" title="Digital imaging">acquisition of an image</a>, typically using cameras, lenses, and lighting that has been designed to provide the differentiation required by subsequent processing.<a href="#cite_note-Handbook427-12">[12]</a><a href="#cite_note-DemantBook-13">[13]</a> MV <a href="Software" title="Software">software</a> packages and programs developed in them then employ various <a href="Digital_image_processing" title="Digital image processing">digital image processing</a> techniques to extract the required information, and often make decisions (such as pass/fail) based on the extracted information.<a href="#cite_note-Handbook429-14">[14]</a>

<div class="mw-heading mw-heading3"><h3 id="Equipment">Equipment</h3></div>

The components of an automatic inspection system usually include lighting, a camera or other imager, a processor, software, and output devices.<a href="#cite_note-AssemblyIntro2016-7">[7]</a>: 11–13

<div class="mw-heading mw-heading3"><h3 id="Imaging">Imaging</h3></div>

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 <a href="Smart_camera" title="Smart camera">smart camera</a> or smart sensor.<a href="#cite_note-15">[15]</a><a href="#cite_note-VSD201302-16">[16]</a> Inclusion of the full processing function into the same enclosure as the camera is often referred to as embedded processing.<a href="#cite_note-PhotonicsSpectra2019-17">[17]</a> When separated, the connection may be made to specialized intermediate hardware, a custom processing appliance, or a <a href="Frame_grabber" title="Frame grabber">frame grabber</a> within a computer using either an analog or standardized digital interface (<a href="Camera_Link" title="Camera Link">Camera Link</a>, <a href="CoaXPress" title="CoaXPress">CoaXPress</a>).<a href="#cite_note-coaxexpress-18">[18]</a><a href="#cite_note-VSDCompliantCameras-19">[19]</a><a href="#cite_note-Davies2nd-20">[20]</a><a href="#cite_note-Dinev-21">[21]</a> MV implementations also use digital cameras capable of direct connections (without a framegrabber) to a computer via <a href="IEEE_1394" title="IEEE 1394">FireWire</a>, <a href="USB" title="USB">USB</a> or <a href="Gigabit_Ethernet" title="Gigabit Ethernet">Gigabit Ethernet</a> interfaces.<a href="#cite_note-Dinev-21">[21]</a><a href="#cite_note-VSDInterfaces-22">[22]</a>

While conventional (2D visible light) imaging is most commonly used in MV, alternatives include <a href="Multispectral_image" class="mw-redirect" title="Multispectral image">multispectral imaging</a>, <a href="Hyperspectral_imaging" title="Hyperspectral imaging">hyperspectral imaging</a>, imaging various infrared bands,<a href="#cite_note-InfraredVSDApril2011-23">[23]</a> line scan imaging, <a href="3D_imaging" class="mw-redirect" title="3D imaging">3D imaging</a> of surfaces and X-ray imaging.<a href="#cite_note-NASAarticle-6">[6]</a> Key differentiations within MV 2D visible light imaging are monochromatic vs. color, <a href="Frame_rate" title="Frame rate">frame rate</a>, resolution, and whether or not the imaging process is simultaneous over the entire image, making it suitable for moving processes.<a href="#cite_note-WestHSRT-24">[24]</a>

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.<a href="#cite_note-DN201202-25">[25]</a><a href="#cite_note-Davies4th410-411-26">[26]</a> 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. 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 <a href="Depth_map" title="Depth map">depth map</a> or point cloud.<a href="#cite_note-QualityMagazine-27">[27]</a> Stereoscopic vision is used in special cases involving unique features present in both views of a pair of cameras.<a href="#cite_note-QualityMagazine-27">[27]</a> Other 3D methods used for machine vision are <a href="Time-of-flight_camera" title="Time-of-flight camera">time of flight</a> and grid based.<a href="#cite_note-QualityMagazine-27">[27]</a><a href="#cite_note-DN201202-25">[25]</a> One method is grid array based systems using pseudorandom structured light system as employed by the Microsoft Kinect system circa 2012.<a href="#cite_note-hybrid-28">[28]</a><a href="#cite_note-pseudorandom-29">[29]</a>

<div class="mw-heading mw-heading3"><h3 id="Image_processing">Image processing</h3></div>

After an image is acquired, it is processed.<a href="#cite_note-Davies2nd-20">[20]</a> Central processing functions are generally done by a <a href="CPU" class="mw-redirect" title="CPU">CPU</a>, a <a href="GPU" class="mw-redirect" title="GPU">GPU</a>, a <a href="FPGA" class="mw-redirect" title="FPGA">FPGA</a> or a combination of these.<a href="#cite_note-PhotonicsSpectra2019-17">[17]</a> Deep learning training and inference impose higher processing performance requirements.<a href="#cite_note-VSDSept2019-30">[30]</a> Multiple stages of processing are generally used in a sequence that ends up as a desired result. A typical sequence might start with tools such as filters which modify the image, followed by extraction of objects, then extraction (e.g. measurements, reading of codes) of data from those objects, followed by communicating that data, or comparing it against target values to create and communicate "pass/fail" results. Machine vision image processing methods include;

<ul><li><a href="Image_stitching" title="Image stitching">Stitching</a>/<a href="Image_registration" title="Image registration">Registration</a>: Combining of adjacent 2D or 3D images.</li>

<li>Filtering (e.g. <a href="Morphological_image_processing" class="mw-redirect" title="Morphological image processing">morphological filtering</a>)<a href="#cite_note-Demant39-31">[31]</a></li>

<li>Thresholding: Thresholding starts with setting or determining a gray value that will be useful for the following steps. The value is then used to separate portions of the image, and sometimes to transform each portion of the image to simply black and white based on whether it is below or above that grayscale value.<a href="#cite_note-Demant96-32">[32]</a></li>

<li>Pixel counting: counts the number of light or dark <a href="Pixel" title="Pixel">pixels</a></li>

<li><a href="Segmentation_(image_processing)" class="mw-redirect" title="Segmentation (image processing)">Segmentation</a>: Partitioning a <a href="Digital_image" title="Digital image">digital image</a> into multiple <a href="Image_segment" class="mw-redirect" title="Image segment">segments</a> to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.<a href="#cite_note-computervision-33">[33]</a><a href="#cite_note-34">[34]</a></li>

<li><a href="Edge_detection" title="Edge detection">Edge detection</a>: finding object edges<a href="#cite_note-Demant108-35">[35]</a></li>

<li>Color Analysis: Identify parts, products and items using color, assess quality from color, and isolate <a href="Feature_(computer_vision)" title="Feature (computer vision)">features</a> using color.<a href="#cite_note-NASAarticle-6">[6]</a></li>

<li><a href="Blob_extraction" class="mw-redirect" title="Blob extraction">Blob detection and extraction</a>: inspecting an image for discrete blobs of connected pixels (e.g. a black hole in a grey object) as image landmarks.<a href="#cite_note-Demant95-36">[36]</a></li>

<li><a href="Artificial_neural_network" class="mw-redirect" title="Artificial neural network">Neural network</a> / <a href="Deep_learning" title="Deep learning">deep learning</a> / <a href="Machine_learning" title="Machine learning">machine learning</a> processing: weighted and self-training multi-variable decision making<a href="#cite_note-TurekNeuralNet-37">[37]</a> Circa 2019 there is a large expansion of this, using deep learning and machine learning to significantly expand machine vision capabilities. The most common result of such processing is classification. Examples of classification are object identification,"pass fail" classification of identified objects and OCR.<a href="#cite_note-TurekNeuralNet-37">[37]</a></li>

<li><a href="Pattern_recognition" title="Pattern recognition">Pattern recognition</a> including <a href="Template_matching" title="Template matching">template matching</a>. Finding, matching, and/or counting specific patterns. This may include location of an object that may be rotated, partially hidden by another object, or varying in size.<a href="#cite_note-Demant111-38">[38]</a></li>

<li><a href="Barcode" title="Barcode">Barcode</a>, <a href="Data_Matrix" title="Data Matrix">Data Matrix</a> and "<a href="2D_barcode" class="mw-redirect" title="2D barcode">2D barcode</a>" reading<a href="#cite_note-Demant125-39">[39]</a></li>

<li><a href="Optical_character_recognition" title="Optical character recognition">Optical character recognition</a>: automated reading of text such as serial numbers<a href="#cite_note-Demant132-40">[40]</a></li>

<li><a href="Metrology" title="Metrology">Gauging/Metrology</a>: measurement of object dimensions (e.g. in <a href="Pixel" title="Pixel">pixels</a>, <a href="Inch" title="Inch">inches</a> or <a href="Millimeter" class="mw-redirect" title="Millimeter">millimeters</a>)<a href="#cite_note-Demant191-41">[41]</a></li>

<li>Comparison against target values to determine a "pass or fail" or "go/no go" result. For example, with code or bar code verification, the read value is compared to the stored target value. For gauging, a measurement is compared against the proper value and tolerances. For verification of alpha-numberic codes, the OCR'd value is compared to the proper or target value. For inspection for blemishes, the measured size of the blemishes may be compared to the maximums allowed by quality standards.<a href="#cite_note-Demant125-39">[39]</a></li></ul>

<div class="mw-heading mw-heading3"><h3 id="Outputs">Outputs</h3></div>

A common output from automatic inspection systems is pass/fail decisions.<a href="#cite_note-Handbook429-14">[14]</a> These decisions may in turn trigger mechanisms that reject failed items or sound an alarm. Other common outputs include object position and orientation information for robot guidance systems.<a href="#cite_note-NASAarticle-6">[6]</a> Additionally, output types include numerical measurement data, data read from codes and characters, counts and classification of objects, displays of the process or results, stored images, alarms from automated space monitoring MV systems, and <a href="Process_control" class="mw-redirect" title="Process control">process control</a> signals.<a href="#cite_note-WestRoadmap-10">[10]</a><a href="#cite_note-DemantBook-13">[13]</a> This also includes user interfaces, interfaces for the integration of multi-component systems and automated data interchange.<a href="#cite_note-Handbook709-42">[42]</a>

<div class="mw-heading mw-heading2"><h2 id="Deep_learning">Deep learning</h2></div>

The term <a href="Deep_learning" title="Deep learning">deep learning</a> has variable meanings, most of which can be applied to techniques used in machine vision for over 20 years. However the usage of the term in "machine vision" began in the later 2010s with the advent of the capability to successfully apply such techniques to entire images in the industrial machine vision space.<a href="#cite_note-qualitymag2022-43">[43]</a> Conventional machine vision usually requires the "physics" phase of a machine vision automatic inspection solution to create reliable simple differentiation of defects. An example of "simple" differentiation is that the defects are dark and the good parts of the product are light. A common reason why some applications were not doable was when it was impossible to achieve the "simple"; deep learning removes this requirement, in essence "seeing" the object more as a human does, making it now possible to accomplish those automatic applications.<a href="#cite_note-qualitymag2022-43">[43]</a> The system learns from a large amount of images during a training phase and then executes the inspection during run-time use which is called "inference".<a href="#cite_note-qualitymag2022-43">[43]</a>

<div class="mw-heading mw-heading2"><h2 id="Imaging_based_robot_guidance">Imaging based robot guidance</h2></div>

Machine vision commonly provides location and orientation information to a robot to allow the robot to properly grasp the product. This capability is also used to guide motion that is simpler than robots, such as a 1 or 2 axis motion controller.<a href="#cite_note-NASAarticle-6">[6]</a> The overall process includes planning the details of the requirements and project, and then creating a solution. This section describes the technical process that occurs during the operation of the solution. Many of the process steps are the same as with automatic inspection except with a focus on providing position and orientation information as the result.<a href="#cite_note-NASAarticle-6">[6]</a>

<div class="mw-heading mw-heading2"><h2 id="Market">Market</h2></div>

As recently as 2006, one industry consultant reported that MV represented a $1.5 billion market in North America.<a href="#cite_note-Hapgood46-44">[44]</a> However, the editor-in-chief of an MV trade magazine asserted that "machine vision is not an industry per se" but rather "the integration of technologies and products that provide services or applications that benefit true industries such as automotive or consumer goods manufacturing, agriculture, and defense."<a href="#cite_note-Holton-4">[4]</a>

<ul><li><a href="Machine_vision_glossary" class="mw-redirect" title="Machine vision glossary">Machine vision glossary</a></li>

<li><a href="Feature_detection_(computer_vision)" class="mw-redirect" title="Feature detection (computer vision)">Feature detection (computer vision)</a></li>

<li><a href="Foreground_detection" title="Foreground detection">Foreground detection</a></li>

<li><a href="Vision_processing_unit" title="Vision processing unit">Vision processing unit</a></li>

<li><a href="Optical_sorting" title="Optical sorting">Optical sorting</a></li></ul>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

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</style><div id="Emerging_technologies167" style="font-size:114%;margin:0 4em"><a href="Emerging_technologies" title="Emerging technologies">Emerging technologies</a></div></th></tr><tr><th scope="row" class="navbox-group" style="text-align: center;;width:1%">Fields</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%;text-align: center;"><div style="display: inline-block; line-height: 1.2em; padding: .1em 0;"><a href="Information_and_communications_technology" title="Information and communications technology">Information and communications</a></div></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Internet_of_things" title="Internet of things">Internet of things</a></li>

<li><a href="Artificial_intelligence" title="Artificial intelligence">Artificial intelligence</a>

<ul><li><a href="Applications_of_artificial_intelligence" title="Applications of artificial intelligence">Applications of artificial intelligence</a></li>

<li><a href="Machine_translation" title="Machine translation">Machine translation</a></li>

<li><a href="Mobile_translation" title="Mobile translation">Mobile translation</a></li>

<li><a href="Progress_in_artificial_intelligence" title="Progress in artificial intelligence">Progress in artificial intelligence</a></li>

<li><a href="Speech_recognition" title="Speech recognition">Speech recognition</a></li></ul></li>

<li><a href="Atomtronics" title="Atomtronics">Atomtronics</a></li>

<li><a href="Carbon_nanotube_field-effect_transistor" title="Carbon nanotube field-effect transistor">Carbon nanotube field-effect transistor</a></li>

<li><a href="Cybermethodology" title="Cybermethodology">Cybermethodology</a></li>

<li><a href="Augmented_reality" title="Augmented reality">Augmented reality</a></li>

<li><a href="Optical_disc#Fourth-generation" title="Optical disc">Fourth-generation optical discs</a>

<ul><li><a href="3D_optical_data_storage" title="3D optical data storage">3D optical data storage</a></li>

<li><a href="Holographic_data_storage" title="Holographic data storage">Holographic data storage</a></li></ul></li>

<li><a href="General-purpose_computing_on_graphics_processing_units" title="General-purpose computing on graphics processing units">GPGPU</a></li>

<li>Memory

<ul><li><a href="Programmable_metallization_cell" title="Programmable metallization cell">CBRAM</a></li>

<li><a href="Electrochemical_RAM" title="Electrochemical RAM">ECRAM</a></li>

<li><a href="Millipede_memory" title="Millipede memory">Millipede</a></li>

<li><a href="Racetrack_memory" title="Racetrack memory">Racetrack memory</a></li>

<li><a href="SONOS" title="SONOS">SONOS</a></li>

<li><a href="UltraRAM" title="UltraRAM">UltraRAM</a></li></ul></li>

<li><a href="Optical_computing" title="Optical computing">Optical computing</a></li>

<ul><li><a href="Chipless_RFID" title="Chipless RFID">Chipless RFID</a></li></ul></li>

<li><a href="Software-defined_radio" title="Software-defined radio">Software-defined radio</a></li>

<li><a href="Three-dimensional_integrated_circuit" title="Three-dimensional integrated circuit">Three-dimensional integrated circuit</a></li></ul>

</div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="text-align: center;;width:1%">Topics</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Automation" title="Automation">Automation</a></li>

<li><a href="Collingridge_dilemma" title="Collingridge dilemma">Collingridge dilemma</a></li>

<li><a href="Differential_technological_development" title="Differential technological development">Differential technological development</a></li>

<li><a href="Disruptive_innovation" title="Disruptive innovation">Disruptive innovation</a></li>

<li><a href="Ephemeralization" title="Ephemeralization">Ephemeralization</a></li>

<li><a href="Ethics_of_technology" title="Ethics of technology">Ethics</a>

<li><a href="Bioethics" title="Bioethics">Bioethics</a></li>

<li><a href="Cyberethics" title="Cyberethics">Cyberethics</a></li>

<li><a href="Neuroethics" title="Neuroethics">Neuroethics</a></li>

<li><a href="Robot_ethics" title="Robot ethics">Robot ethics</a></li></ul></li>

<li><a href="Exploratory_engineering" title="Exploratory engineering">Exploratory engineering</a></li>

<li><a href="Proactionary_principle" title="Proactionary principle">Proactionary principle</a></li>

<li><a href="Technological_change" title="Technological change">Technological change</a>

<ul><li><a href="Technological_unemployment" title="Technological unemployment">Technological unemployment</a></li></ul></li>

<li><a href="Technological_convergence" title="Technological convergence">Technological convergence</a></li>

<li><a href="Technological_evolution" title="Technological evolution">Technological evolution</a></li>

<li><a href="Technological_paradigm" title="Technological paradigm">Technological paradigm</a></li>

<li><a href="Technology_forecasting" title="Technology forecasting">Technology forecasting</a>

<ul><li><a href="Accelerating_change" title="Accelerating change">Accelerating change</a></li>

<li><a href="Future-oriented_technology_analysis" title="Future-oriented technology analysis">Future-oriented technology analysis</a></li>

<li><a href="Horizon_scanning" title="Horizon scanning">Horizon scanning</a></li>

<li><a href="Moore's_law" title="Moore's law">Moore's law</a></li>

<li><a href="Technological_singularity" title="Technological singularity">Technological singularity</a></li>

<li><a href="Technology_scouting" title="Technology scouting">Technology scouting</a></li></ul></li>

<li><a href="Technology_in_science_fiction" title="Technology in science fiction">Technology in science fiction</a></li>

<li><a href="Technology_readiness_level" title="Technology readiness level">Technology readiness level</a></li>

<li><a href="Technology_roadmap" title="Technology roadmap">Technology roadmap</a></li>

<li><a href="Transhumanism" title="Transhumanism">Transhumanism</a></li></ul>

</div></td></tr><tr><td class="navbox-abovebelow" colspan="2" style="text-align: center;"><div>

</div></td></tr></tbody></table></div>

<div class="navbox-styles"></div><div role="navigation" class="navbox" aria-labelledby="Glossaries_of_science_and_engineering45" style="padding:3px"><table class="nowraplinks hlist mw-collapsible autocollapse navbox-inner" style="border-spacing:0;background:transparent;color:inherit"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Glossaries_of_science_and_engineering45" style="font-size:114%;margin:0 4em">Glossaries of <a href="Science" title="Science">science</a> and <a href="Engineering" title="Engineering">engineering</a></div></th></tr><tr><td colspan="2" class="navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Glossary_of_aerospace_engineering" title="Glossary of aerospace engineering">Aerospace engineering</a></li>

<li><a href="Glossary_of_agriculture" title="Glossary of agriculture">Agriculture</a></li>

<li><a href="Glossary_of_archaeology" title="Glossary of archaeology">Archaeology</a></li>

<li><a href="Glossary_of_architecture" title="Glossary of architecture">Architecture</a></li>

<li><a href="Glossary_of_artificial_intelligence" title="Glossary of artificial intelligence">Artificial intelligence</a></li>

<li><a href="Glossary_of_astronomy" title="Glossary of astronomy">Astronomy</a></li>

<li><a href="Glossary_of_biology" title="Glossary of biology">Biology</a></li>

<li><a href="Glossary_of_botanical_terms" title="Glossary of botanical terms">Botany</a></li>

<li><a href="Glossary_of_calculus" title="Glossary of calculus">Calculus</a></li>

<li><a href="Glossary_of_cell_biology" class="mw-redirect" title="Glossary of cell biology">Cell biology</a></li>

<li>Cellular and molecular biology

<li><a href="Glossary_of_chemistry_terms" title="Glossary of chemistry terms">Chemistry</a></li>

<li><a href="Glossary_of_civil_engineering" title="Glossary of civil engineering">Civil engineering</a></li>

<li><a href="Glossary_of_clinical_research" title="Glossary of clinical research">Clinical research</a></li>

<li><a href="Glossary_of_computer_hardware_terms" title="Glossary of computer hardware terms">Computer hardware</a></li>

<li><a href="Glossary_of_computer_science" title="Glossary of computer science">Computer science</a></li>

<li><a href="Glossary_of_developmental_biology" title="Glossary of developmental biology">Developmental and reproductive biology</a></li>

<li><a href="Glossary_of_ecology" title="Glossary of ecology">Ecology</a></li>

<li><a href="Glossary_of_economics" title="Glossary of economics">Economics</a></li>

<li><a href="Glossary_of_electrical_and_electronics_engineering" title="Glossary of electrical and electronics engineering">Electrical and electronics engineering</a></li>

<li>Engineering

<li><a href="Glossary_of_entomology_terms" title="Glossary of entomology terms">Entomology</a></li>

<li><a href="Glossary_of_environmental_science" title="Glossary of environmental science">Environmental science</a></li>

<li><a href="Glossary_of_genetics_and_evolutionary_biology" title="Glossary of genetics and evolutionary biology">Genetics and evolutionary biology</a></li>

<li>Geography

<li><a href="Glossary_of_Arabic_toponyms" title="Glossary of Arabic toponyms">Arabic toponyms</a></li>

<li><a href="Glossary_of_Hebrew_toponyms" title="Glossary of Hebrew toponyms">Hebrew toponyms</a></li>

<li><a href="Oikonyms_in_Western_and_South_Asia" title="Oikonyms in Western and South Asia">Western and South Asia</a></li></ul></li>

<li><a href="Glossary_of_geology" title="Glossary of geology">Geology</a></li>

<li><a href="Glossary_of_ichthyology" title="Glossary of ichthyology">Ichthyology</a></li>

<li><a href="Glossary_of_machine_vision" title="Glossary of machine vision">Machine vision</a></li>

<li><a href="Glossary_of_areas_of_mathematics" title="Glossary of areas of mathematics">Mathematics</a></li>

<li><a href="Glossary_of_mechanical_engineering" title="Glossary of mechanical engineering">Mechanical engineering</a></li>

<li><a href="Glossary_of_medicine" title="Glossary of medicine">Medicine</a></li>

<li><a href="Glossary_of_meteorology" title="Glossary of meteorology">Meteorology</a></li>

<li><a href="Glossary_of_mycology" title="Glossary of mycology">Mycology</a></li>

<li><a href="Glossary_of_nanotechnology" title="Glossary of nanotechnology">Nanotechnology</a></li>

<li><a href="Glossary_of_bird_terms" title="Glossary of bird terms">Ornithology</a></li>

<li><a href="Glossary_of_physics" title="Glossary of physics">Physics</a></li>

<li><a href="Glossary_of_probability_and_statistics" title="Glossary of probability and statistics">Probability and statistics</a></li>

<li><a href="Glossary_of_psychiatry" title="Glossary of psychiatry">Psychiatry</a></li>

<li><a href="Glossary_of_quantum_computing" title="Glossary of quantum computing">Quantum computing</a></li>

<li><a href="Glossary_of_robotics" title="Glossary of robotics">Robotics</a></li>

<li><a href="Glossary_of_scientific_naming" title="Glossary of scientific naming">Scientific naming</a></li>

<li><a href="Glossary_of_structural_engineering" title="Glossary of structural engineering">Structural engineering</a></li>

<li><a href="Glossary_of_virology" title="Glossary of virology">Virology</a></li></ul>

</div></td></tr></tbody></table></div>

<div class="navbox-styles"></div><div role="navigation" class="navbox authority-control" aria-labelledby="Authority_control_databases_frameless&#124;text-top&#124;10px&#124;alt=Edit_this_at_Wikidata&#124;link=https&#58;//www.wikidata.org/wiki/Q1425977#identifiers&#124;class=noprint&#124;Edit_this_at_Wikidata530" style="padding:3px"><table class="nowraplinks hlist mw-collapsible autocollapse navbox-inner" style="border-spacing:0;background:transparent;color:inherit"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><div id="Authority_control_databases_frameless&#124;text-top&#124;10px&#124;alt=Edit_this_at_Wikidata&#124;link=https&#58;//www.wikidata.org/wiki/Q1425977#identifiers&#124;class=noprint&#124;Edit_this_at_Wikidata530" style="font-size:114%;margin:0 4em">Authority control databases </div></th></tr><tr><th scope="row" class="navbox-group" style="width:1%">National</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"><ul><li><a rel="nofollow" class="external text" href="https://d-nb.info/gnd/4202022-0">Germany</a></li></ul></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Other</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"><ul><li><a rel="nofollow" class="external text" href="https://lux.collections.yale.edu/view/concept/b405e7db-60a4-4f4d-afe9-ec98e78de2de">Yale LUX</a></li></ul></div></td></tr></tbody></table></div></div><div><div class="zim-footer">

This article is issued from <a class="external text" title="Last edited on 2025-07-23" href="https://en.wikipedia.org/wiki/?title=Machine_vision&oldid=1302060470">Wikipedia</a>. The text is available under <a class="external text" href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">Creative Commons Attribution-Share Alike 4.0</a> unless otherwise noted. Additional terms may apply for the media files.

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