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Denzel Vieta

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Basics of image processing in AI


The term image processing has been widely discussed ever since the boom in the Artificial Intelligence industry. Many new startups are mainly focused on image processing. Not only that, but these starts are also registering great profits out of these image processing projects.

Before getting started with the basics of image processing, let's discuss why this industry is booming?

There are many big players already working in this industry. These big players are Google, Microsoft, Azure, Facebook(Meta), and many others. As these players invest millions of dollars in this industry, it opens doors for more research. There is a saying in economics, the more the funding is there for industry, it will grow faster than the overall GDP. For that reason, this industry is rising at such a speed.

Along with that, all the code written for an Artificial Intelligence product is open source. Open source means that anyone can use this code and make changes without asking for permission or anything else. This helps small start-ups and individuals to make something creative with the help of this code.

Which programming language is the best for AI?

Undoubtedly Python programming language comes first for an AI app development project. As discussed above Python is an open-source programming language that has several libraries that can be helpful to develop an image processing app. If you learn the python programming language then you can have a higher probability of finding your desired job. Apart from Python, node.js is also a good option for image processing projects. It has several open-source libraries called node packages. But node.js is mainly used for web development purposes and you might have a lesser chance of getting a full-time job if you learn Node.js for image processing.

The basics of image processing

A normal image is in the form of RGB form. RGB is represented in the hexadecimal numbers. The CSS color code is also described in the hexadecimal numbers. You need to convert hex to number in order to read and understand.

A typical machine cannot read the image in form of RGB as there is a hexadecimal number. To resolve this issue, the image processing engineer needs to convert this image into a greyscale image. After converting this into a grey image, a machine inherits the ability to recognize all the objects in an image.

Once this is performed, you need to apply logic to count all four coordinates on an image. This helps in making the image read properly by the machine.

So, this is a detailed explanation of image processing. Do share your thoughts about this by commenting on this article below.


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