Taking A Look At Computer Vision and its Applications

Hello, guys today we take a look at computer vision and its applications. Computer vision is an emerging field and it brings numerous applications to our daily life. Looking at this technology and by the end of the article, you will be in a position to explain the need for computer vision.

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Brief History of Computer vision.

Introduction to Computer vision

In general Computer Vision is a field that aims to come up with computational models of the human visual system.

Applications of Computer Vision

CV in Self driving Cars

This is one field that Computer vision is necessary. In order to move you need to know where you are going. You need to understand the path the direction and the road to use this is making sense of the environment. Now imagine a car that can do all that.

Self-driving cars are able to make sense of their surroundings by using computer vision. This is made possible by the use of cameras that captures videos from the car surrounding. The videos are then fed into a computer that analyzes them in real-time to find the nature of the roads, read the traffic lights, detect objects on the road. With all this information the car is able to make decisions on what path to follow and avoid obstacles and follow the traffic rules. CV makes a car drive itself.

CV in Healthcare

The medical sector is another field that computer vision plays an important role. Imagine a scenario when a doctor wants to examine your internal organs like the stomach and cuts you open in order to find out the cause of the problem. In this case, it is expensive and life-risking this is where Computer vision comes into play. Instead of the Doctor performing an operation they use a camera to get a view of the internal parts of the body. In other cases the use of ultrasound to monitor the internal body organs.

An image of an X-ray under examination one application of computer vision in health care.

Computer vision algorithms in health care will help you understand ultrasound scans, detecting cancerous moles in skin images, finding symptoms in x-ray, and MRI scans.

Image and Facial Recognition

This is used mostly in security systems. Computer vision identifies the features of an image, runs a check on the face profile database and compares the images. The algorithms match the images therefore identifying the identity of an image. The most basic application of computer vision is the face unlock feature in most phones. The phone identifies the owner by understanding basic features of the face uses that in future to identify the owner.

Augmented Reality, Virtual Reality and Mixed reality

According to Wikipedia AR is the modification of a real-life environment by the addition of sound and visual elements enhanced by computer-generated perceptual information. Mixed reality is the merging of real and virtual worlds to produce a new environment and visualization, where physical and digital objects co-exist and interact in real time.

Virtual reality.

Virtual reality (VR) is a simulated experience that can be similar to or completely different from the real world.

Computer vision enables a computer to obtain, process, analyze an image or video. CV drives Virtual Reality, Augmented Reality and the Mixed reality.

Social media Content Moderation

Social media platforms need to restrict the kind of content that is posted given the high number of users this task needs to be fast yet reliable. Computer vision comes in and enables the regulation of content this removes photos that contain violence, extremism, or pornography. Most platforms use deep-learning algorithms are to analyze posts and flag those that contain banned content.

CV in sports

In today sports like football we can see the integration of CV. The most common is the VAR the goal line technology. Computer vision in sports is changing the experience of the game by ensuring a fair result at the end of the game.

Virtual Assistant Referee in use.
  • CV in the industries
  • CV in military
  • Predictive Maintenance
  • Object tracking
  • Instance segmentation

Summary

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