Machine vision



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  1. What is Machine Vision?

Machine vision (MV) 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 in industry. The scope of MV is broad. MV is related to, though distinct from, computer vision.

Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. A theme in the development of this field has been to duplicate the abilities of human vision by electronically perceiving and understanding an image. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. Computer vision has also been described as the enterprise of automating and integrating a wide range of processes and representations for vision perception.

Machine vision has become a key technology in the area of manufacturing and quality control due to the increasing quality demands of manufacturers and customers. Machine vision utilizes industrial image processing through the use of cameras mounted over production lines and cells in order to visually inspect products in real time without operator intervention.

Machine vision (also called "industrial vision" or "vision systems") is primarily focused on computer vision in the context of industrial manufacturing processes, be it in the inspection process itself (e.g. checking a measurement or identifying a character string is printed correctly) or through some other responsive input needed for control (e.g. robot control or type verification). The machine vision system can consist of a number of cameras all capturing, interpreting and signalling individually with a control system related to some pre-determined tolerance or requirement.

Machine vision encompasses computer science, optics, mechanical engineering, and industrial automation. Unlike computer vision which is mainly focused on machine-based image processing, machine vision integrates image capture systems with digital input/output devices and computer networks to provide real time quality control and for general control of manufacturing equipment such as robots. Manufacturers favour machine vision systems for visual inspections that require high-speed, high-magnification, 24-hour operation, and/or repeatability of measurements.

Components of a machine vision system?

A typical machine vision system will be part of an automated production process consisting of the following components:

very specialized, light sources.

A typical machine vision system will be part of an automated production process consisting of the following components:

 

- One or more digital cameras (monochrome or color) with suitable optics for acquiring images, such as lenses to focus the desired field of view onto the image sensor and suitable, often very specialized, light sources.



- A synchronizing sensor for part detection (often an optical or magnetic sensor) to trigger image acquisition and processing and some form of actuators to sort, route or reject defective parts.
- A computer program (normally running on the latest Windows 7 OS) to process images, detect, measure, compare etc in order to confirm a quality criteria has been met or to provide type verification or robot control to another control system.

- Input/Output hardware (e.g. digital I/O) or communication links (e.g. Industrial Ethernet, ProfiBUS etc) to report results and to automatically reject components.

("Intelligent" or "smart" cameras combine the above into a single unit).

 

The aim of a machine vision inspection system is typically to check the compliance of a test piece with certain requirements, such as prescribed dimensions, serial numbers, presence of components, etc. The complete task can frequently be subdivided into independent stages, each checking a specific criterion.




Types on inspection tasks


The mst common use for deploying machine vision is to perform the following tasks:

- Position recognition

- Identification (by codes, characters etc.)

- Shape and dimension checks

- Completeness checks

- Image and object comparison

- Surface inspection


  1. What are the differences between Machine Vision and Image Processing?

CV applications range from tasks such as industrial machine vision systems which, say, inspect bottles speeding by on a production line, to research into artificial intelligence and computers or robots that can comprehend the world around them. 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 industrial applications.

Machine Vision Uses


Vision systems can be applied in almost any industry. Historically the first systems were deployed in the semi-conductor and automotive industries due to their high intensive use of industrial automation within these industries. Modern vision systems can be applied across a hugely diverse range of industry sectors, these industries include:

 

- Automotive



- Semi-conductor

- Electronics

- Medical Devices and Pharmaceutical

- Printing and Packaging

- General Mechanical Engineering

- Food Processing

- Solar Production


  1. What are the main companies working on Computer Vision?






The Computer Vision Industry 

David Lowe


This web page lists companies that develop computer vision products. Computer vision (also often referred to as "machine vision" for industrial vision applications) is the automated extraction of information from images. This differs from image processing, in which an image is processed to produce another image. This page covers only products based on computer vision, and it does not cover image processing or any of the many suppliers of sensors or other equipment to the industry.

Companies are categorized under their principal application area, and then listed alphabetically. Companies are listed only if they have web pages giving information about their products. Please let me know of any links that are missing.



Automotive driver assistance and traffic management 


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