Computer vision is a technology or a field that encapsulates various methods for gathering, analyzing and interpreting images. This analysis leads to producing or delivering numerical or symbolic information. The means computer vision can be applied to different applications to carry out different activities with efficiency. When you think of Computer Vision, you usually think of Virtual Reality or Facial Recognition. Companies like Oculus Rift and Magic Leap stand out at the forefront of the virtual reality space. Facefirst and Facebook are companies that employ facial recognition software to make their products even better. Computer vision can also help in other fields like agriculture, biotechnology, and the car industry.
Improvements in computer vision have improved the way crops get analyzed. For example, normalized difference vegetation index (NDVI) is calculated by measuring the intensity of visible and near-infrared light reflected by the land surface. It quantifies the amount of vegetation on a land surface. Soil scientists, agronomists, and farmers make use of this computer vision technique to predict the annual crop yield.
Computer vision has also played a major part in assessing properties in biotechnology systems. Often times the texture or color has a correlation with properties in biotech systems. For example, turbidity of a bacteria culture grown in a flask has a high correlation with the amount of growth of the bacteria culture. Knowing that fact has allowed biotech professionals to combine computer vision with existing technology to engineer devices like a spectrophotometer or tweak mobile phones to measure the growth. Companies like Thermo Fisher Scientific specialize in designing and manufacturing devices like a spectrophotometer. A little-known company called Bioeye has developed software to give a mobile device similar measurement capabilities as a spectrophotometer using image processing.
Computer vision has revolutionized the car industry by making cars autonomous. An autonomous car is a car that senses and navigates the road without any human interference. A large amount of high fidelity visual sensors has been mounted on theses vehicles to allow them to drive vehicles safer than humans. For example, camera sensors to detect traffic lights, infrared sensors to avoid pedestrians, and sonar sensors to avoid collisions. In March 2016, California passed a bill that allows autonomous cars to operate on the road, so it is just a matter of time before all cars on the road will be fully autonomous. Until that time, a lot of vehicles were just employing collision avoidance systems like Mobileye to keep passengers safe.
The advancements in computer vision have tremendously helped other fields in tech. Applications and devices from companies in the tech industry have reaped a lot of the benefits by applying the techniques developed. In the future, computer vision will be more present in our day to day lives.