Operations carried out on a particular image, whether or not it is digital, so as to deliver an enhanced version of the image. In fact, this method is often used as a tool to extract necessary information from an image. Image Processing falls under the category of Signal Processing, where the information that is put in is an image. However, the output can be just an image or the different characteristics that are in association with that particular image. This technology, growing at an incredibly fast pace, is one of the core areas of research in both the disciplines of engineering and computer science. 

Image Processing step by step

The whole method is actually a combination of three distinct steps – first importing(sourcing) the image that is going to undergo processing, then follows the acquiring of the required tools for the job and finally comes the analysis of the image, to see what needs to be done to the image(image manipulation). Image Processing can be performed both as an analog method or a digital method. The former finds use in the processing of printouts and other types of hard copies of images(photographs). 

Applications of image processing: 

In the digital version of image processing, the first thing to do is to complete the conversion of signals received from an image sensor and then turn the input into a digitized image(s). 

Image Processing can actually be used for –

  • Improving the clarity of a particular image through the removal of noise in the image and any other problems for example high hand graphics tools and animations media. For example in case there is a static sound or a radio sound in the background, it can be canceled or eliminated. 
  • Finding out the actual size of an object, it’s a scale or the number of the objects in a particular image can be done using Image Processing. For example: in a picture, it is always either bigger or smaller than the actual size of the object thus, image processing can help to trace the original size of the object. It can be highly useful for forensics and detective agencies. 
  • Digital Image Processing allows for images to be compressed into smaller sizes to make it easier to send them over the internet. It saves a lot of cost and Mb.  
  • Turning images into photographs by printing them is another important solution provided by Image Processing. It is helpful in case of projects and presentations. 
  • Data is the new oil so image processing is a mechanism producing new oil. 
  • Handling the cashing device-specific using different – different pixels. 
  • Image compression for reducing the network and storage burdon.

Though Image Processing started off in the early days as a way to increase the clarity of an image, it has branched out to a lot of different processes and is still increasing in scope owing to the advent of digitization of the whole process. On the other hand, the whole process of image processing is done digitally, with manipulation of the image done all on computers. Digital Image Processing starts with pre-processing, leading to enhancing the picture and then displaying the extracted information in the end. 

Uses of image processing in Machine Learning: 

Nowadays machine learning is a buzz word but this just not a buzz word it solve lot’s of real world challenges in an efficient manner. 

Application of image processing using machine learning: 

  1. Image Classification 
  2. Emotion Classification 
  3. Real-time face deduction and intention prediction 
  4. Real-time headcount and motion follow 
  5. Croud specific  Adwords campaigns 
  6. Handwriting identifier – human written writing understanding
  7. Human less cars 
  8. Smart parking 
  9. The smart toll for vehicle size and weight-based toll collection 
  10. Speed capturing and predictions and many more.