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Machine vision 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 refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise.
In computer vision, blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to surrounding regions. Informally, a blob is a region of an image in which some properties are constant or approximately constant; all the points in a blob can be considered in some sense ...
The computer vision and machine vision fields have significant overlap. Computer vision covers the core technology of automated image analysis which is used in many fields. Machine vision usually refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in ...
In 2003, he published a widely-read booklet titled The Cognitive Style of PowerPoint, revised in 2006. [19] Tufte found a number of problems with the "cognitive style" of PowerPoint, many of which he attributed to the standard default style templates: [19] PowerPoint's convenience for some presenters is costly to the content and the audience.
Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [ 2 ] navigation of mobile robots , [ 3 ] or edge detection in images.
EMVA1288 [1] is an electronic measurement standard developed by the European Machine Vision Association (EMVA). Its purpose is to define the methods to measure and characterize image sensors and cameras that are used in machine vision. It also provides rules and guidelines on how to report results and how to write device datasheets.
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