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Laboratory Virtual Instrument Engineering Workbench (LabVIEW) [1]: 3 is a graphical system design and development platform produced and distributed by National Instruments, based on a programming environment that uses a visual programming language.
A simple custom block in the Snap! visual programming language, which is based on Scratch, calculating the sum of all numbers with values between a and b. In computing, a visual programming language (visual programming system, VPL, or, VPS), also known as diagrammatic programming, [1] [2] graphical programming or block coding, is a programming language that lets users create programs by ...
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 ...
LabWindows/CVI uses the same libraries and data-acquisition modules as the better known National Instrument product LabVIEW and is thus highly compatible with it. LabVIEW is targeted more at domain experts and scientists, and CVI more towards software engineers that are more comfortable with text-based linear languages such as C.
Data acquisition applications are usually controlled by software programs developed using various general purpose programming languages such as Assembly, BASIC, C, C++, C#, Fortran, Java, LabVIEW, Lisp, Pascal, etc. Stand-alone data acquisition systems are often called data loggers.
The following outline is provided as an overview of and topical guide to computer vision: Computer vision – interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
In computer vision and image processing, Otsu's method, named after Nobuyuki Otsu (大津展之, Ōtsu Nobuyuki), is used to perform automatic image thresholding. [1] In the simplest form, the algorithm returns a single intensity threshold that separate pixels into two classes, foreground and background.
Computer stereo vision is the extraction of 3D information from digital images, such as those obtained by a CCD camera. By comparing information about a scene from two vantage points, 3D information can be extracted by examining the relative positions of objects in the two panels.