Humans can understand pictorial information with ease. When we see a picture, we can pick up some information about the scene which has been clicked. We can identify the people in the photo, the scenery, the colours, and the arrangement.
A computer, however, treats all the photos as an array of pixels, having numerical values for Red, Green, Blue (RGB) coefficients. It cannot work out the smaller details in any photo as humans do. Since the last seven to eight decades, considerable efforts have been put to make computer systems intelligent enough to make sense out of visual data.
What is Computer Vision?
Computer Vision can be described as a field of study concerned with the development of algorithms that can make computers “see” and try to understand the content of the images or videos. It is a multidisciplinary field that combines AI with machine learning.
It tries to automate the process which is carried out by the Human Vision System. The study of Computer Vision began in the 1960s intending to mimic the Human Vision system so that intelligent robots could be bestowed with their vision.
Computer vision has been termed as one of the most trending subtopics in the field of artificial intelligence. The human vision system has been powered by billions of years of evolution, along with years of experience. Computers only understand numbers. So, for them, making sense of visual data is a tough task. Many companies are actively working to make Computer Vision solutions accessible.
The Need for Computer Vision
The question now arises, why do computers need to “see” the images. Every minute, the internet is being flooded with millions of images. There is at least 100GB of video information added to YouTube every minute. There is no shortage of videos and photos on the internet.
It is effortless to search for textual data, but search for videos or images becomes difficult. However, visual data is not understood by the computer system, and the descriptions which the uploader has put are used to make sense out of this data. Computer Vision helps the machine categorize the images, which helps us reach accurate search results.
Hardware Required
Most of the Computer Vision systems have three basic requirements:
- A power source,
- A camera, and
- An interpreting device.
There might be added hardware requirements considering the use-case, but the basic requirements remain the same for all Computer Vision Solutions.
How can Computer Vision help?
Computer Vision is a complex process, having many applications in various industries.
- Computer Vision allows an accurate image or video search results on any search engine.
- Facial recognition systems are used to establish the identity of people. They can be used in many industries for various purposes, which includes security, e-challan generation, self-checkout counters, etc. Artificial Intelligence development companies have launched products to be used at malls, offices or homes. The Police Department also uses Computer Vision Solutions in their automated traffic management systems.
- Healthcare services have used computer vision to improve the diagnostic process. Images generated from MRIs, CT Scans, X-rays, etc. can be read by the machine to detect the possible anomalies.
- People who are visually impaired can use computer vision assisted setups that can be used to guide them to navigate indoors safely.
- Driverless cars make use of Computer Vision for object detection. Nearly all automobile companies have roped in Artificial Intelligence Development Services to help create intelligent cars that will be able to drive themselves.
- Military uses this technology to collect information about enemy territory. Use of computer vision in self-guided missiles has allowed the destruction of potential threats accurately.
Conclusion
The development in this field has been on the rise. Artificial Intelligence Development Services are trying to incorporate Computer Vision in their solutions to real-world problems. In the days to come, we might see Computer Vision bringing the next revolution in the field of AI.