Introduction to Computer Vision
Before entering the article, please get in touch with Convolutional neural networks because CNN is the algorithm behind Computer vision implementation. Introduction to Convolutional neural networks.
In the image below we can visualize the objects with our naked eye and name them as Butterfly, and Marigold flower. Human vision is amazingly beautiful and complex. It all started millions of years ago when small organisms developed a mutation and that made them sensitive to light. At present, life is abundant on our planet which all have a very similar vision. Our visual system includes the eyes for capturing light, receptors in the brain for accessing it, and the visual cortex for processing it. This is the basic nature of any visual system.
In the past few years, we have developed even more by extending this amazing visual system not just to ourselves but to the machines as well. Nowadays with our present technology, we can closely mimic how the human eye can capture light and color. It has become the easiest part nowadays with the help of the cameras. But to understand what’s in the image is much more difficult.
Let’s consider the below image, my human brain can look at it and immediately know that it is a flower since our brain has a million years of experience. But the computer doesn’t have that same advantage so we need an algorithm for a machine to understand this image. The image on the right side shows the pixel form that a machine understands. To an algorithm, the image looks like this just a massive array of integers that represent intensities across the color spectrum. Here comes the Computer vision into play. Let’s see what is important and the applications of computer vision in real life.
Computer vision is the most useful and powerful technology in Artificial intelligence. We use Computer vision in our daily life without even knowing about it.
Let’s delve in and know more about Computer vision and how it works, and its importance in the real world.
Computer vision is one of the subfields of computer science and it deals with images and videos and tries to replicate the human visual system on the machines. The main aim of Computer vision is to give computers the ability to extract high-level understanding from digital images and videos.
With time everything evolves similarly to computer vision. With the help of Deep Learning and Neural networks computer vision has developed a lot and has become much easier now. Before the Deep learning era, human has to perform a lot of manual work besides using computer vision. The driving force behind the development of computer vision is the amount of data that we will produce daily. This training of a large amount of data led to the growth of Computer vision. Along with the software, there has been a huge development in the hardware that supports the present technology.
Working of Computer Vision:
We know that neural networks try to mimic the human brain and solve many advanced problems easily. Similarly, computer vision tries to mimic the human visual system. To be precise computer vision is all about pattern recognition.
What computer vision does is that it helps the computer to understand the visual data that we feed as images while training. Here comes the various algorithms which try to identify the pattern that is present within the data.
Example: Consider a set of images let’s suppose images in this case be flowers. We have a million images of flowers and what computer vision here does is that it feeds these images as inputs to all the algorithms. These algorithms analyze the color, shape, and distances between the parts of images. With the help of this analysis, a system stores the profile of how a particular flower looks. After storing the data our computer will be able to use this experience while identifying other images.
Computer vision indirectly deciphers the image. Earlier it is much difficult for a machine to decode the information present in an image, but now it has become super-fast with the help of computer vision.
Applications of Computer Vision:
Any place where the resources are used more efficiently is a place where technology can play a role. But of course, one of the most impactful technologies we use nowadays is AI and computer vision is the main factor behind AI. So, now let’s see the applications of computer vision in our daily lives.
- Self-Driving Cars: Nowadays many companies are launching self-driving cars. Computer vision helps to sense the surroundings of the vehicle. The cameras installed in the car capture the videos from all directions and feed them to a computer vision software. The software analyses those videos and find the margins of the road, traffic signals, detects the other vehicles and pedestrians. With the help of self-driving cars, we can reduce the percentage of accidents that are happening daily.
- Medical Care: Computer vision has a wide range of applications in the medical department. It automatically detects dangerous diseases like cancer with the help of moles on the skin or by x-ray images.
- Facial Recognition: Facial recognition is one of the most important applications of computer vision. Here computer vision helps the system to compare the people’s images to their original identities in their database. Mainly we can see facial recognition in social media it helps us to tag people by recognizing their faces.
- Augmented Reality: Computer vision helps the computing devices like tablets, smartphones, VRs to display virtual objects in the real imaginary world.
This article helps you to understand how computer vision works and the importance of computer vision in daily life.
Thanks for reading!