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An Easy-to-Understand Guide on Computer Vision

The fantasy of simulating the human visual system by a machine is outdated. The technology world has come a long way to interpreting and understanding the visual world. Computer vision has made it possible for machines to bring some of the most innovative technology to life. Today, computer vision is one of the hottest trends in the fields of machine learning and artificial intelligence, considering its tremendous potential and a wide variety of applications.

From smartphone applications that identify animals to precision farming and contactless food delivery, computer vision leverages visual data to introduce innovative solutions and disrupt varied industries.

Let’s understand more about the concept of computer vision and how it is benefitting the real world.

A quick introduction to Computer Vision

From self-driving cars to the detection of manufacturing defects, computer vision is helping modern businesses to solve visual tasks. We interact with data, algorithms, and computer vision applications every day like using a contactless delivery service or shopping in a retail store. For example, scanning a QR code to show movie tickets or scanning a retail receipt to get a refund or reimbursement.

Computer vision is a subfield of Artificial Intelligence (AI) where computers can see the visuals and interpret them. It utilizes visual data from the real world, and machines are taught to identify the objects, take action, or decide based on the visuals.

Computer vision translates the visual content into clear descriptions to gather data. And this data is further turned into a computer-readable language that helps in making relevant decisions.

Applications of Computer Vision

Especially in the manufacturing and automotive sector, computer vision offers several applications such as

In the manufacturing sector, it is useful for automated assembly of products, defects detection, Computer vision-guided die-cutting, barcode analysis, 3D vision system, predictive machine maintenance, safety and security standards, real-time inventory management.

The automotive sector can use computer vision applications for the detection of the parts’ position and orientation, recognition of welding defects, gauging inspection, regular checks of wheels and electric components, monitoring of power-train assembly, vehicle performance analysis, detection of safety components.

Why is computer vision important?

From selfies to professional images, we are flooded with a lot of visuals today. According to a report on Internet trends, over 1.8 billion images are uploaded on the internet every day. And this is just the number of images uploaded, imagine the number of images stored on mobile devices. All this visual content needs to be analyzed and understood smartly. Computer vision helps in teaching the machines how to see the images and videos. It uses algorithms to read the images and index them automatically. Most of the popular platforms like Google and YouTube use computer vision to scan images and videos to feature the content, provide relevant content to the users, and protect against online toxicity.

How does computer vision work?

Computer vision relies on the techniques of pattern recognition to understand and self-train the visual content. Earlier, computer vision applications used machine learning algorithms but now, they use deep learning methods as a better solution in this domain.

For example, machine learning requires a huge amount of data and human monitoring to ensure the accuracy of results. Now, deep learning relies on neural networks and uses problem-solving examples. It self-learns by labeling the data and recognizing the common patterns in the examples.

Use Cases of Computer Vision

Some of the most popular use cases of computer vision applications include

  • Machine inspection
  • Medical imaging
  • Motion capture
  • Optical character recognition
  • Surveillance
  • Face and fingerprint recognition
  • Automotive safety
  • Personalized retail automation
  • Computer-generated imagery

Industry applications

Humans can also understand the scenes corresponding to images, interpret paintings and handwriting. But computervision technology possesses a wide range of practical applications across various industries. Let’s look at some of the top industry applications of computer vision technology.


Most of the manufacturing firms are concerned with the breaking of machines, defective components of the machines resulting in significant losses. Computer vision technology proves to be a great solution for predictive maintenance. It analyses the visual information and algorithms to identify the potential problems before they occur. These solutions also help in spotting defects in components throughout the line of production. It allows manufacturers to take real-time action and make the right decisions to resolve the problems.


There are a variety of impressive applications of computer vision in the healthcare domain. And medical image analysis is one of the best-known examples as it significantly improves the process of media diagnosis. The images from X-rays, MRIs, and CT scans are analyzed to find anomalies and illnesses. So, computer vision plays a vital role in analyzing the images and extracting the features from images to train a classifier to detect anomalies. There are many more applications that are currently used in the healthcare domain like quantification of coronary artery calcium, estimation of the amount of blood lost in hemorrhages, and evaluation of blood flow in the human body.


Self-driving cars are not a new concept in this era. Computer vision technology plays a huge role in the automotive industry as it enables the perception and understanding of the environment and operates correctly. Computer vision also helps in locating various objects and classifying them to distinguish if the objects are a car, a traffic light, or a person. When this technology is combined with the data analysis capabilities of sensors or radars, it allows the vehicles to see and drive automatically.

Media and entertainment

Computer vision helps in leveraging augmented reality and virtual reality. Conventional media channels like TV and radio don’t require users to participate. But today, interactive media provides a whole new level of experience. Now is the time of animation, moving images and graphics, and interactive videos. Consumers can command the media by using controllers, be it Google glass, smartphone, or eyewear. All such amazing experiences are driven by the combination of computer vision technology, real-time camera source, and image synthesis. Moreover, interactive media is also applied to ensure a smart and tech-enabled learning process.

Moving towards the right approach to computer vision

Computer vision has gained a lot of attention from a wide range of industries. The computer vision market is expected to be worth USD 48 Billion by 2023! With the increasing amount of data, it is natural that machines will use the data to craft innovative solutions.

If you want to leverage computer vision technology for your firm, you are only a click away. Reach out to us to get the best solution for your business.

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