Table of Contents
How machine vision works
Common applications of machine vision
The Difference Between Machine Vision and Computer Vision
Home Technology peripherals AI Machine Vision vs. Computer Vision: Definitions and Differences

Machine Vision vs. Computer Vision: Definitions and Differences

Jan 23, 2024 am 08:42 AM
computer vision

Machine Vision vs. Computer Vision: Definitions and Differences

There are some differences between machine vision and computer vision. Machine vision is mainly used in industrial fields such as automatic inspection and manufacturing processes. It uses image capture and processing technology to define actions. Computer vision, on the other hand, is more broadly concerned with the capture and analysis of images, and has a wider range of applications. Machine vision can be seen as a subset of computer vision, responsible for completing tasks such as image analysis. Overall, there is some overlap between machine vision and computer vision, but there are some differences in applications and functionality.

How machine vision works

The main components of a machine vision system include lighting, lenses, image sensors, vision processing, and communications.

To ensure that lighting illuminates the part to be inspected so that target features stand out, the lens needs to be able to capture them clearly. The lens converts the captured image into a light signal, which is then passed to the sensor in machine vision. The sensor converts the light signal into a digital image and sends it to the processor for analysis. The vision processing system reviews the image, extracts the required information, and runs the necessary inspection algorithms to make decisions. Finally, the information is sent via discrete I/O signals or serial connections to the device that records or uses the information.

Common applications of machine vision

Machine vision has a wide range of practical applications and is of great significance. It can be used to inspect objects, find defects in objects and check the integrity of packaging. Machine vision systems can also be programmed to implement functions such as object classification, color detection and verification, pattern recognition and matching. In addition, machine vision can read barcodes in structured environments. These applications make machine vision play an important role in manufacturing, logistics and security fields.

The Difference Between Machine Vision and Computer Vision

While both machine vision and computer vision involve ingesting and analyzing visual input, there are differences between the two has a difference.

Machine vision systems use digital cameras to capture images and then process them to output decisions. These decisions include pass-fail decisions in the production line based on defects detected by the vision system. Machine vision systems also typically include cameras, lenses, processors and software to enable the machine to make these decisions. In other words, machine vision is part of a larger machine system.

The computer vision system can be used alone. Unlike machine vision systems, computer vision systems do not require cameras. So computer vision doesn't necessarily need to capture the image, it can directly process the saved image. Computer vision systems can interpret data and produce results from saved images. Computer vision has more flexibility in this regard, as it can work by using real or synthetic images.

Computer vision systems can derive valuable information from images, videos, and other visuals, while machine vision systems rely on images captured by the system's cameras.

Another difference is that computer vision systems are typically designed to extract and use as much data as possible. In contrast, machine vision typically focuses on specific key parts of an object and then processes the data captured by the image. Because machine vision is used more for finding specific data information, machine vision often makes quick decisions in a controlled environment.

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