In most cases, computer vision and vision are thought to be the same, but these two different conditions apply to overlapping technologies.
Computer vision generally refers to recording information and analyzing image stored with emphasis on image analysis function in a wide range of theoretical and practical applications.
Where does the Machine vision come in?
The machine vision traditionally refers to the use of computer vision in processes or industrial applications in which a specific function or result is required based on the analysis of the image stored by it.The visual system is programmed to identify predetermined features using the software.This system can be used to create a set of “actions” based on findings.
For example, in a bottling plant in the food and drink industry, machine vision can be used to identify bugs in several ways. This can help identify the damage to the bottle easily. It can be used to determine the level of filling bottles to determine the correct location of the label on the bottle. To diagnose the correct installation of bottle caps in place, it can also check all items on the bottle label. The system can take the necessary action depending on which software is used to code the information. For example, you can send certain products to a special packaging line, or remove defective products from the product line or return to the beginning of the line for re-examination.
The main components of computer vision and vision are usually the same:
- A imaging device, usually a camera, contains an imaging sensor and a lens.
- Used to capture an electronic board or frame grabber (Some digital cameras use a modern interface and do not need frame grabber.)
- Light suitable for various applications
- A computer, but in some cases, like a smart camera, where all the processes are happening on the camera and do not require a computer.
- Image processing software
The lines of computer vision and Machine vision in the past few years have become weaker, machine vision is also used in non-industrial environments, including biomedicine or life sciences, and even trying to improve web searches on the image.