TOP 10+ Application of Computer Vision

Application of Computer Vision : Computer Vision (CV) is the capacity of computers to perceive, and predict images and videos. Almost every business sector uses CV, which is transforming the way industries work.

Application of Computer Vision
Application of Computer Vision

Almost all companies have adopted Computer Vision, and the demand for CV and similar technologies had been rising very fast. Its ability to solve problems on a large scale, accurately, quickly, and in an affordable manner is the primary reason for its fast pace and growth.

With computer power becoming affordable and portable, an increasing number of computer vision applications for businesses, smart-city surveillance, health service, automobile industries, and analytical imaging tools. etc.

Application of Computer Vision in Various Field

Application of Computer Vision
Application of Computer Vision


E-Commerce is a buzzword across the globe these days. One of the most important functions of e-commerce is automatic product categorization. Whenever a new product is made available on the e-commerce store, its aspects are automatically updated with the help of the Computer Vision system without any human intervention. It helps the products to go up on virtual shelves and within the consumer’s reach faster.


Banking is primarily concerned with security and customer service. Facial recognition can be helpful with these services. Progressive banks are making use of Computer Vision for applying KYC (Know Your Customer) processes.

Computer Vision helps customers to open accounts by uploading photographs and documents, and by making a video call. Enhanced level of customer satisfaction and simplification of creating accounts directly impact a bank’s revenues.


In the healthcare sector Computer Vision has helped in more accurate reading of MRI and CT scans. It is also enhancing radiology procedures, helping doctors, nurses, and other healthcare specialists in treating their patients, and increasing the survival rates of patients with fatal conditions.

Image-based Diagnostics

The use of Computer Vision technology in the medical field to examine scan reports and identify patterns may hint at the probability of medical conditions.

Interactive Medical Imaging

CV and deep learning can help in reading and converting 2D scan images into interactive 3D models. This will help healthcare professionals to achieve a deeper understanding of patients’ health conditions.


Most advanced cars use accident prevention systems. These systems depend on computer Vision technology and they can perceive the road, feel where the lanes are sense if there are vehicles or people nearby, and understand other surrounding objects to avoid accidents, warm the driver, and in some cases automatically apply brakes. Facial recognition systems can also warn the driver if he feels sleepy while driving a vehicle.

Application of Computer in AUTOMOTIVE INDUSTRY
Application of Computer in AUTOMOTIVE INDUSTRY


The insurance sector comprises many small segments. There are different types of insurance products available, like home, automotive, health fire, and asset insurance. Whatever may be the type of products, the challenges that the insurance sector faces as a whole are almost the same.


In today’s scenario, social media platforms have become a big source of images and videos. Nearly 95 million images and videos are uploaded to Facebook every day. It is not possible to handle and process such as huge amount of data manually.

Computer Vision can process images automatically by identifying brand logos very fast, understanding optimal color patterns for various markets, and searching for the subject of images. CV helps companies to satisfy targeted markets in a more personalized way.


Computer Vision helps identify customers buying habits in stores and assists in the process of placing products on the shelves where they can be easily discovered resulting in better sales.

Amazon appliances CV technology to automatically identify what people have purchased from their store for an automated and easy shopping experience.

8. Manufacturing

In the manufacturing sector, one of the important applications related to Computer vision is to perform predictive maintenance. Computer vision helps in reducing downtime in this case.

With the help of the photos attained through CCTV cameras, it is easier to foresee which machine is most likely to have a breakdown. In response to the data received, necessary maintenance can be done and necessary spare parts can be arranged beforehand.


In the field of sports, Computer Vision can track the moment of the players. Better analysis and insights are now generated live to help players and managers enhance their performance. This also enhances game-watching experiences, and the accuracy of referees, and yields better player performance.


In the logistics industry, CV is being used to fount and track inventory more accurately, leading to better accountability. We can also use it to check the quality of the packaging. Optical Character Recognition (OCR) is used for reading the text printed on the labels of packages.

CV and Machine Learning technologies in the supply chain industry help in rebuilding customer experience and automating human tasks. Al-based solutions assist supply chain managers to avoid hazards and financial losses.


Farmers are using Al and similar sophisticated technology to enhance their operations. Technology is helping farmers to find out the most efficient cultivation method, increase production, and control waste.

is an agriculture-based company using a CV to increase productivity? Slan Range installs CV-enabled cameras onto drones. These drones are used to scan crops and give relevant information to the farmers.


In recent times, Intelligent Transportation Systems (ITS) have received substantial research attention in areas, like vehicle detection, recognition, counting, traffic parameter estimation, etc.

Vision sensors offer more information than the conventional sensors widely used in ITS, and therefore, attention is now concentrated on vision-based traffic surveillance systems.This project hopes the development of an actual traffic surveillance system for the detection, recognition, and tracking of multiple vehicles in traffic videos.

Traffic signal light optimization using vehicle flow statistics, identification of speed violations, vehicle density estimation, occlusive vehicle detection/ recognition, and incident detection are some of the features that can be made a part of this framework.

So that’s all about Application of Computer Vision.

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