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Machine vision is a technology that allows machines to emulate the ability of human vision. Common applications are in the manufacturing industry in order to automate processes with cameras, in medical imaging for guidance during surgery, in drones and self-driving cars, in robotics for navigation or picking, and also appear in consumer products such as smart TVs or smartphones. This article will discuss the different types of machine vision, which are necessary to understand the applications.

Machine vision can basically be divided into two major categories: active and passive imaging.

In passive imaging, light is emitted by the scene itself. For example, in night-vision equipment, infrared light is reflected from objects and detected by the camera.

The vast majority of machine vision systems use active illumination, where an external source of illumination is used to light up the scene. This source of illumination can be anything that emits electromagnetic waves within the visible spectrum, such as a white or colored light bulb, an LED, or a laser diode. There are also machines that emit X-rays and/or gamma rays, but they appear less frequently due to their potentially hazardous nature.

Machine Vision can be roughly divided into two major categories: Imaging and non-imaging.

A camera is the most common machine vision tool because it enables computer vision systems to see and interpret images in order to solve tasks such as quality control or object detection. The main advantage of a camera system is that it can provide real-time video images, while other systems can only provide images when they are activated and programmed to do so.

A laser scanner is a special type of camera that projects a laser pattern onto the scene in order to scan it. The system will then interpret this pattern and extract information from it such as the distance or the color of objects within the scene.

A motion sensor is a type of camera that measures changes in the environment to determine if something has moved, for example, due to the presence of an intruder. Motion sensors are often used as part of security systems because they can send an alert with video footage when movement is detected, but they are also widely used in industrial automation for safety purposes. Typical applications are in assembly lines or the horticulture industry where they monitor for broken fences or potential collisions with obstacles.

Can be paired with a camera to create an automatic counter, counting the number of people who pass by at a given time, for example, to determine foot traffic volume.

In industrial automation, machine vision guides robots to perform tasks such as inspection or picking and placing. Robots that execute these routine tasks can be placed at different locations in the production environment, but to do their job properly they need to use machine vision to position themselves within a scene and locate objects such as defective products, empty places where workpieces should be placed, or tools for other machines.

Machine vision can be used to inspect parts for defects during production. For example, it can signal the presence of contaminants on a surface by using image processing algorithms to find edges or places where the color changes sharply. It can also check if all parts are present and aligned correctly before the finished product leaves the factory floor.

The quality of manufactured products can be greatly improved by using machine vision to track the process throughout production. The system can monitor if machines are working properly, if tools or workpieces need to be replaced, or if there is human action needed for certain tasks.

Machine vision can be used as part of a robot navigation system so that it can find its way around without bumping into people or obstacles. The system uses a laser rangefinder to detect the distance between itself and surrounding objects, which are then represented in 3D space. This information allows the robot to move around without colliding with its surroundings or triggering an emergency stop button on the production line.

Conclusion

In conclusion,  machine vision systems have become a mainstay of modern production processes because they help solve common problems such as counting objects, detecting defective parts, or checking for correct placement. In many applications, machine vision is the only solution that allows for automated inspection and/or detection to occur in real-time.

By admin

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