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Computer vision explained: It is not just image recognition!

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Artificial Intelligence

The terms ‘Image Recognition’ and ‘Computer Vision’ are often used interchangeably but are actually different. In fact, Image Recognition is an application of Computer Vision that includes a set of tasks. Simply put, Image Recognition is a subset of Computer Vision. Therefore, we decided to explain the difference between the two terms in this blog.

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Also Read: 5 Ways in Which AI/ML is Transforming Insurance

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What is Computer Vision?

It is a field that seeks to develop techniques to help computers see and understand the content of digital images such as photographs and videos. It uses Artificial Intelligence (AI) that trains computers to interpret and understand the visual world. Machines can accurately identify as well as locate objects and then react to what they “see” using deep learning models.

Technically, machines attempt to retrieve visual information and interpret results through special software algorithms.

Source – Adobe

Here are a few common tasks that computer vision systems can be used for:

  • Object classification – This involves classifying the objects in the videos and photos in different categories. For example, the system can find a cat among all objects in the image / video.
  • Object identification – The system analyses visual content and identifies a particular object on a photo/video. For example, the system can find a specific person among the group of people in the image.
  • Object tracking – The system processes video and finds the object / person that match search criteria and track its movement.

Source – Towards data science

Whereas, Image Recognition is the process of identifying an object or a feature in an image or video. It is a subcategory of Computer Vision. It is used in many applications like defect detection, medical imaging, and security surveillance.

How does Image Recognition work?

Source – My Great Learning

A digital image is an image composed of picture elements, also known as pixels. So the computer sees an image as numerical values of these pixels and in order to recognise a certain image, it has to recognise the patterns and regularities in this numerical data.

Wrapping up

Computer vision is a popular topic in articles about new technology. It is more than simply seeing things. Its potential is superhuman to be able to see clearly in the dark, through walls, over long distances, and process all of the data quickly and in large volume. A different approach to using data is what makes this technology different. Data can teach computers to see and understand objects. The emergence of AI opens the way to new development for businesses. More and more, companies are using Computer Vision and its subset Image Recognition to improve their processes and increase their productivity.

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