What are the definition of computer vision and its usage?

by Sudarsan

Computer vision is a completely new development that is actively gaining popularity.  Therefore, today we will talk about it in more detail.

To take advantage of new technologies, you need to find good specialists, such as Unicsoft – an artificial intelligence development company.

Computer vision is an interdisciplinary field of research that deals with understanding how computers can reproduce the proceedings and functions of the human visual apparatus.  Thus, not only to acquire static or moving images (even outside the spectrum of natural light), to identify them, to recognize and extract useful information for decision-making: digital depiction machining is only a section of computer vision.  The part that falls precisely into the early vision, the “low level of abstraction” processing, on which, since the 1960s, numerous steps forward have been made.  The most ambitious task of computer vision concerns high-level vision, “at a high level of abstraction and realization”, which forms a 2D image that can process, reconstruct and analyze the entire 3D context in which the image is inserted.  That is, it may give historical and contextual meaning, and so symbolic, to the picture it presents.

Characteristics of computer’s vision work

Every digital image can be decomposed into dots, pixels, the smallest units of the image surface, arranged differently on a grid, 2D (grayscale), or 3D (color) matrix.  The size of the image depends on the number of rows and columns of the matrix, color the image by a number or a triad of numbers associated with each pixel.  Between zero-black and 255-white for grayscale images instead of a triad of red, green, and blue intensities for color images.  This type of representation is called a raster.

Another type of representation of a digital image is a vector: the image is given by mathematical equations that can describe not only points but also lines, segments, triangles, the so-called geometric primitives.  In both the “raster” and “vector” cases, the computer “sees” any image as a set of numbers.

In an artificial vision system, image acquisition begins with a sensor that generates an output signal and sends it to a computer that digitizes and stores it.  The image is then “read” and, depending on the purposes of analysis for which the system has been programmed, is first “pre-processed” by the software or made “suitable” for analysis and then processed.  Then the result of the analysis is compared with the reference model, classified, and used for decision-making.

“Artificial vision” refers to industrial applications.  Machine vision is used in any industrial environment with a significant degree of automation, where product specifications are clearly defined, and mass production takes place.  This includes the automotive industry, the semiconductor industry, and the electronics industry in general.  Sometimes a computer vision system is connected to a robotic arm that rejects defective products or even actively participates in the production of a product.

A computer vision system typically consists of a pressure or optical sensor, a camera, a lighting system, a central processing unit (CPU), associated imaging software, and an I/O system for connecting to a wider network.

If the artificial vision system is located next to the conveyor belt, as is often the case, the sequence of events is as follows: a pressure sensor or an optical sensor is triggered when the product moves in front of the camera, a light pulse is triggered to illuminate the target, the camera performs the exposure, and the image is processed and fed into the tree solutions, which returns a result, which is then triggered by an automatic element or displayed to the operator.  This simple process can automate the classification or verification of thousands of products every day, saving millions of hours of work.

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