A guide to AI based image processing: Phases, techniques and tools

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ai based image processing | iTMunch

The method of manipulating images to either extract relevant information from it or enhance its quality is called image processing. Image processing is extremely useful and its demand is continuously growing. The market for image recognition is projected to grow to US$38.92 billion in 2021 at a CAGR of 19.5% [1]. Thanks to the recent advancements in technology, artificial intelligence can be used in image processing. In this blog, we’ll talk about digital image processing, the phases of AI based image processing and a few tools and techniques you can use for the same. 

Historically speaking, image processing that utilizes machine learning appeared first in the 1960s. It was an attempt to simulate the human vision system as well as automate the image analysis process. As the image processing technology developed and enhanced, radical solutions for specific tasks began to emerge, and soon AI in image processing also began gaining popularity. 

Now, let us begin by understanding what is image processing.

What is image processing?

Generally speaking, image processing is the method of performing operations on images, in order to obtain enhanced images or to extract information from it. There are two ways of image processing:

  • Analog image processing: Traditional image processing that’s used for processing physical photographs, hard copies of images and printouts 
  • Digital image processing: Used for manipulating digital images by using computer algorithms like machine learning and artificial intelligence 

In both cases, analog and digital, the input is the same (an image). However, for analog image processing, the output will always be an image, but for digital image processing, output might be an enhanced image of information associated with that image. This information can be data on characteristics, features, masks or bounding boxes.

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