• Claire Matuka

Real life Applications of Computer Vision



Welcome to Part 2 of the Computer Vision series. In Part 1; Introduction to Computer Vision, we defined what Computer Vision (CV) is, its benefits as well as its history.


So, how exactly does a computer that can "see" and understand images, help me and others around the world?


It is highly likely that you have encountered some application of Computer Vision in your day to day life, either knowingly or unknowingly. Some of these applications have become so normal that we barely notice them. This article will shed a light on them.


Applications of Computer Vision

There are several applications of computer vision today. They range from object recognition, image search, optical character recognition, 3D reconstruction, image de-noising and even augmented reality.


1. Object Recognition

Object recognition is a CV technique that is used to identify objects in images, videos and visual inputs. I find this to be one of the most commonly used and explored CV applications. The objects being identified can range from pets (cats and dogs), to food (burgers, fries, rice) and any other object you can think of.


Ever heard of facial recognition? I bet you have. If you are reading this on your phone, I can even bet that you unlocked your phone using it. Most smartphones today match an image or video to a stored image, as a form of authentication. We can say that the object being identified in this case is the human face.



Self driving cars have been the talk of town. So many car companies are currently investing in developing them, with Tesla being the most popular. In all honesty, I want a Tesla, you want a Tesla, everyone wants a Tesla (Dear Oprah, can everyone get a Tesla please). Self driving cars are able to "see" objects such as other cars, pedestrians, traffic signals, road markers, objects such as cones, etc. It is the ability to see these objects, coupled with other forms of technology that enables these cars to respond accordingly.


2. Optical Character Recognition

OCR is simply the conversion of images, handwritten texts or even printed text into a machine-readable form.


Whenever you choose to open a pdf document in Google Docs, that is OCR in action.


When I was studying my Bachelor's, I would occasionally have to leave school to go visit my parents. I liked having my books with me but it was so exhausting to constantly have to move around with them. If only I could store my handwritten notes digitally :(

I discovered Evernote, an app that can literally read my handwriting and store my notes. This is also OCR in action.


3. Image Search

Image search is simply technology that allows users to search the web using images instead of just text and get results of similar images.


Online shopping has never been easier than it is today. Thanks to Google Images, if I come across an outfit or even shoes that I like, I can simply search the image and possibly get results of similar outfits or the exact outfit. This way, I can figure out where to buy it.


4. Image de-noising

I must admit, I do not have the best phone camera in the world. Taking photos in environments with low light is actually a nightmare. I often end up with grainy images that are not good to look at. It’s even worse if I try taking an image of my computer screen. There is always so much noise on the image.


Image de-noising is the technical process of removing noise from images. The end result is often a clearer, pleasant to look at image. This is very useful especially when restoring images.



5. Augmented Reality

Augmented Reality (AR) can be described as an immersive experience in which relevant real world information is presented visually thanks to technology.


The Metaverse is expected to have elements of both VR and AR. A number of people believe that the Metaverse is the future of social connection and interaction. AR is bound to be crucial in the future.


Computer vision (CV) for augmented reality enables computers to obtain, process, analyze and understand digital videos and images.


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Conclusion

It is clear that Computer Vision is all around us. Advancements in this field are still ongoing and I cannot wait to see what new applications will emerge. Remember at the beginning when I had a strong gut feeling that you have come across some form of Computer Vision? Well, was I right?


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