What Are the Different Types of Computer Vision Applications?

Computer vision, also known as “machine vision,” is a technology that uses cameras and computers to interpret images. There are many different uses for this technology. Some of the most common computer vision applications are in the medical, industrial, and security fields. Additionally, machine vision is prominent in robotics.
Each application of machine vision has the goal of gathering useful information based on visual clues. The data used in computer vision applications may be from a static source, such as a photograph. This technology can also be used to interpret moving images, including live or pre-recorded action captured through a video camera.

Medical computer vision applications are typically used to process static images. Microscope results, x-ray pictures, and ultrasound images can all be interpreted by this technology. Vision software can be programmed to detect abnormalities in a medical photograph. Computer analysis, for instance, can be used to locate tumors on an x-ray result. Computers are sometimes able to scan medical images and identify potential problems at a faster rate than human technicians.

Industrial applications can also make use of machine vision. Factories often use computer vision to inspect merchandise for defects, or to sort objects based on attributes such as size and color. Some factories use high-resolution cameras to capture extremely detailed images of products. Vision software is then used to automatically locate small fractures or imperfections in the material. This technology is able to view details that are imperceptible to the naked eye.

There are several computer vision applications within the field of security. Computers are able to analyze live video feeds in order to track important patterns. Security checkpoints at airports, for example, sometimes use machine vision to recognize the faces of previously identified, wanted criminals. Vision software is also able to track individuals in a crowd and identify suspicious activity, such as abandoned baggage or loitering.

Robotic systems frequently employ computer vision. Autonomous vehicles, including unmanned aerial vehicles (UAVs) and lunar rovers, often use cameras and computers to analyze the nearby landscape. Prominent terrain features such as mountains can be compared to an electronic map. This allows robotic vehicles to determine their location based on external reference points.

Computer vision is an emerging technology that has not yet reached its full potential. Many scientists believe that in the future, machine vision will lead to advanced technological breakthroughs. Potential applications may be applied to automated cars, unmanned airliners or other technological advances.