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July 28th, 2020

Everything You Ever Wanted To Know About Computer Vision


Computer vision is a powerful field of AI (Artificial Intelligence) that you must have experienced knowingly or unknowingly at least once in your lifetime. Also, the field has grown a lot in recent years due to a lot of advancements as part of artificial intelligence development service and is working well in processing images. Here, we will discuss what is computer vision, how it works, and other related details that one should know about it.

What is Computer Vision?

Computer vision is the part of artificial intelligence development company using which computers get the ability to process any image the same way a human being does. Using this, a computer can identify the objects present in an image, make decisions, and then give the output accordingly. To apply computer vision, the computer sees an image as an array of pixels that represents different colours in the picture. Computer vision today is being used effectively in autonomous vehicles, facial recognition, gesture recognition, and surveillance. Today many companies provide artificial intelligence development services for the development of computer vision.

How Does Computer Vision Work?

The artificial intelligence development service based researchers working on the CV or AI should have a sound knowledge of multiple domains. Below are the different technologies that researchers use in the implementation of CV.

The first step is feature engineering as part of which, the computer converts the image or a video into an array of pixels and then identifies the features such as a blob, corner, and an edge of an object. It is a time-consuming and costly process. But, with the help of deep learning, the process of feature engineering can be automated.

It is necessary to train the computer so that the CV system can be applied. As a part of training the machine, a large number of images are fed to the system, so that system can learn the difference between different objects and differentiate them.

The images that are processed to the machine for training purposes vary according to the domain. As an example, in ophthalmology, the computer needs to diagnose the retina. Therefore the machine is fed with different images of the retina, including the healthy, damaged, and diseased.

Once the machine analyzes the pixels, Computer Vision uses a neural network to predict the content of the image. With each prediction, the computer is fed through the different layers of the neural network many times so that the machine comes with a correct prediction. With multiple processing, the machine comes up with correct predictions in the form of probability. In this way, the artificial intelligence development company is working a lot in the field of computer vision.

The evolution of Computer Vision

Before Deep Learning was developed, Computer Vision tasks were very limited and scientists used to do very much manual coding. For example, to perform facial recognition, in earlier times, scientists had to create a database with images in a specific format and then do a lot of coding for computers to understand the unique features of the object in the images. The next step was to feed the computer new images and the computer will try to identify the face based on the unique features.

With the help of Machine Learning, the coding problem was solved. ML uses algorithms such as linear or logistic regression, support vector machines, and decision trees to find the patterns and detect the objects in the image. Artificial intelligence development service uses a different approach to perform Computer Vision. With neural networks, the computer can extract common patterns to change them into mathematical equations that help in the classification of information. Therefore, Deep Learning provides a great method to do a Computer Vision by using a pre-constructive algorithm and training the machine to detect the phases in the image.

How Long Does It Take To Decipher An Image?

In the past, Super Computers used to perform tasks in days, weeks, or even months, but today with ultra-fast chips in the computers, high-speed internet, and cloud networks, the process has become really fast. The best thing is, the artificial intelligence development service-based companies such as Google, IBM, Facebook, and Microsoft put their Machine Learning works on open source, so that others can use their work to build their own applications. As a result, the other companies using their code, do not need to write all from scratch. As a result, the artificial intelligence development service-based companies working on AI are working together, so that the work that would take weeks to run will get done in 15 minutes. Using the Computer Vision Applications, all this process continues in a few microseconds.

Applications of Computer Vision

Computer vision has found many applications not only in tech-based companies but in many other fields with the help of artificial intelligence development service

Below are some of the applications of the Computer Vision:

CV In Healthcare

Computer vision has made many advances in the field of health care. With the help of CV-enabled machines, doctors can detect different symptoms in MRI Scans and X-rays.

CV In Facial Recognition

Computer vision has found a great application of facial recognition, which is being used by social networking sites and law enforcement agencies to identify the faces. When a CV-enabled machine is fed with the image of a person, it tries to identify the facial features, and then compare these with the thousands of face profiles present in its database.

CV In Self-Driving Cars

Using Computer Vision, a self-driving car can process the surroundings. The camera on the car captures videos of the surroundings from different angles, which are then fed to the CV software. The CV software processes the videos and detects the traffic signs, roads around, other vehicles, and objects. Based on these identifications, the self-driving car identifies its path and avoids hitting obstacles.

CV In Augmented and Mixed Reality

Computer vision plays a crucial role in mixed and augmented reality, as part of which devices like smart glasses, smartphones, and tablets embed virtual objects in the real world. With the help of CV, the object in the real world is detected so that the location of the object on the device’s display is determined, where a virtual object can be placed.

Challenges of Computer Vision

The biggest challenge of computer vision is to train the computer to see and process the image as the human eye does. This is challenging because researchers based on the artificial intelligence development company do not know the complete working of human vision because it involves many things including the perception of the human eye and perception within the human brain. but clearly, all the studies involving the brain have a lot to explore.

The computer vision performs object identification tasks such as object classification, object identification, object verification, object detection, object segmentation, and object recognition. Apart from just identification tasks, it also performs analysis tasks such as video motion analysis to understand the speed of objects in videos, scene reconstruction to create the 3D model of the image, and image restoration to remove the blurred part from the image using ML filters.


As the field of Computer Vision is still growing, it has given impressive applications in different domains. Researchers are still working on the CV to get more insights into its working. However, many research institutes related to the artificial intelligence development company have applied CV, powered by CNNs, and have given some astonishing applications. The future of Computer Vision is very bright, and with more advancements and research, many of the real-world problems will be solved by scientists.

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