Computer vision: the science and technology of machines that see

Computer vision: the science and technology of machines that see

Computer vision: the science and technology of machines that see

The pace at which technology is evolving today has left all other industries behind. So much so, that in order to succeed, it doesn’t matter what sector you belong to. Every company is competing to become a tech company today. Disruptive technologies like Artificial Intelligence , Machine learning, IoT, etc. are leading the digital transformation space. One such branch of technology that falls under the umbrella of AI has gained momentum recently: Computer Vision.

In elementary terms, computer vision entails using software and algorithms backed by machine learning to understand and decipher pixel based visual imagery, both photographs, and videos. While such algorithms have been in place since the early 1960s, they have become way more sophisticated now, especially in the last decade or so. Computer vision aims to replicate the way our brains process images. Neuroscience and machine learning are intimately connected, so this is how it happens. Machines interpret images as pixels with each pixel having a set of color values.

Each image you upload on to a computer, thus, gets decoded into a set of numerical values. Utilizing the power of deep learning, thousands of images are processed by a machine to gain insights and incorporate computer vision. After this is done, the core concepts are then integrated into products that the end consumer uses.
In fact, computer vision has become part and parcel of our daily lives, without us even realizing so. Social media apps have started utilizing a face recognition software to identify people in photos, keep pictures secure and find photos that you have been tagged in. That’s one of the best examples of using computer vision in today’s time. Some algorithms can even assist visually impaired people to see, by describing aloud what the picture looks like. Facebook is just one example. Social media has taken on computer vision to better consumer experience by leaps and bounds, and the results speak for themselves. The face filters that have gained huge popularity within the masses, especially the younger crowd, are also powered by such algorithms.
We live in a world where we have devices that enable fashionistas to take full body selfies. You guessed it right, these devices are also backed by computer vision. The AI algorithm then analyses outfits for them with accessory options along with an overall style rating. Makes life easier, right? That’s is not all. Industries like transport, healthcare , and banking have also realized the value of computer vision and have started implementing it.

Autonomous vehicles are another excellent example of this utility. Since most of the underlying tech in these vehicles rely on the multiple video feeds coming into the car and using computer vision to pick a path. Research has also confirmed that experts have developed a state-of-the-art system for reading retinal fundus images for diabetic retinopathy since most medical diagnosis relies on image processing like X-ray scans, MRI scans, etc. If this can help better the accuracy of such scans, it could go on to save lives and prevent various diseases. And that’s huge potential right there! Coming to the BFSI sector, banks are now using these capabilities to deposit cheques remotely and verify signatures through images. Thus, helping ease the time constraint on transferring funds, and also preventing frauds.

All in all, industries across the spectrum need to embrace technology today if they want to tackle competition face to face. AI and Computer vision have proven to be a tremendous strategic advantage for businesses, and that’s what sets this technology apart. Disruption is the only way ahead, especially concerning technology, and the sooner industries realize this, the better their chances of success are!