Computer Vision Explained Simply: How Machines Learn to See

You take a photo using your phone. Your phone detects the presence of face in the image. It understands the placement of the eyes and also that of the mouth. This isn’t some sort of magic. It’s simply the concept of computer vision.

What Is Computer Vision?

The computer does not see. When humans see a dog, they perceive it as a creature with four paws, a tail, and a wet nose. However, what the computer perceives is a set of numbers corresponding to pixels and their colors. Tens of thousands, maybe even millions of them. Then the computer must discern whether this collection of numbers represents a dog or not.

Humans tried, in some way, to define rules that would help the computer differentiate between dog and not dog. Such as: “if the thing has four legs and fur, then it is a dog”. Next, somebody showed the computer a cat, and all the rules were used yet again. The algorithm failed. Once again. The solution? To train the algorithm by showing it one million dogs and one million not-dogs.

Why Rules Don’t Work

Your smartphone unlocks by recognizing your face. This is computer vision. But it doesn’t really analyze your entire face. It measures the distance between your eyes, nose, and mouth. Essentially a face map. And then verifies whether the person using the smartphone matches that face map.

Medical image analysis. A physician studies an X-ray. The computer could also analyze the same X-ray. It could detect something as small as a tumor, which the fatigued radiologist overlooked. No replacement of doctors. Just an aid to them.

Learning from Data in Computer Vision

Computer vision technology is still prone to attacks. Small alterations within visual perception like stickers on traffic signs may cause the machine to misclassify images. Also, bias within the training datasets may decrease accuracy within minority groups.

Real-World Applications of Computer Vision

In addition, computer vision requires lots of examples. For example, when children see two cats, they will know what is a cat. In order to learn what is a cat for computers, they require millions of examples. Also, when they see unusual things such as a dog having three legs or a cat with one eye, they get confused.

The Future of Computer Vision

More advanced cameras. Higher processing speed. Data becomes more intelligent each year. Soon, your fridge may detect that you have run out of milk and put it on your shopping list. Your doorbell will know who you are and grant you access without even opening the door. It is not here yet, but we are almost there. And when it arrives, it will be seamless.

Conclusion

In conclusion, computer vision stands out among other fields of artificial intelligence, being invisible to the naked eye. Computer vision is used widely and affects many vital areas which may eventually lead to a revolution in the relationship between machines and the material environment. While computer vision may be overlooked at times, it plays a huge role in the industry, and controlling its implementation cannot be overstated.