Computer vision has been defined as a computer possibility to “feel” environment and to sort images or videos, according to the given options. This type of perception covers all actions done by biological vision systems, such as identification or visualization of a certain object located near or in front of the camera. All this data is gathered in a certain form of a document that can be used in other processes. This multidisciplinary program replicates and robotizes collected information, using computers, sensors, and machine learning algorithms.
So, generally, the term computer vision also means artificial intelligence integration in the process of identifying all of all objects, located in the nearest area.
This process can be integrated into many aspects of modern human life. The first association with this term, that comes to a mind, its virtual reality or facial recognition. Both terms are very common for people in the 21st century. Projects, related to virtual reality, are being developed by such companies as Oculus Rift and Magic Leap. Facial recognition is integrated into services, run by Facefirst or Facebook. And, of course, Apple Inc. Besides all of the above, computer vision will be useful in other fields like agriculture, biotechnology, and the car industry.
Biotechnology
Very often in the biotech industry, the texture and color of a forming or formed object are mainly related to properties. For example, the muddiness of a bacteria culture, that was raised in a flask, has high interaction with the amount of its’ growth. This fact was taken into consideration by biotech professionals and they decided to integrate computer vision into a functioning process spectrophotometer or tweak mobile phones to measure the growth.
Agriculture
Introduction computer vision to processes, related to farming and many other aspects of agriculture, has improved crop analysis a lot. We can use as an example, the pattern of calculating normalized difference vegetation index (NDVI). It identifies the amount of vegetation on a land surface. Farmers and agronomists use computer vision in order to predict the amount of crop they will be able to collect every year.
Cars
One of the main challenges, that computer vision has brought to our lives is making cars autonomous. Meaning, a car is able to function without human intervention. A vehicle, that was designed with computer vision sensors, can navigate the road with partial participation of a driver. Of course, a car is not a robot, and they need to have a driver inside in order to control all systems. Nowadays, autopilot is the most popular implementation of computer vision among car enthusiasts. For example, Tesla Motors. Any of the Tesla vehicles, which have Autopilot in their system, can stay within its lane, moving autonomously along the road, avoid collisions with braking and taxiing, find a parking place and park, adjust its speed depending on traffic intensity, including until the vehicle stops and rebuild at the request of the driver, just turn on the turn signal.
The process of integrating computer vision into technology has influenced in a positive way to this field. The products only benefited from this action. In the future, computer vision will be more present in our day to day lives.
