Computer vision is an algorithm that is used in most of the platforms without knowing that it is computer-vision that is making it run so efficiently. To cite a few, facial recognition technology, autonomous vehicles such as cars, drones or ships, and medical image analysis are some of the sectors where computer vision is used to smooth the processing experience.
One must be thinking, how does computer vision work and how does computer-vision come into picture? That being said, let us discuss computer-vision a bit.
What is computer vision?
Computer vision’s key feature is that it has the ability to enable computers to analyze and interpret various visual contents just like the human brain does. Visual contents such as reading text (handwritten or typed text in various fonts), recognizing faces and objects, or understanding the data of videos or images.
To enhance its accuracy and efficiency, computer-vision also uses artificial intelligence techniques such as machine learning or deep learning. Through machine learning, computer vision can train computers to identify various patterns such as shapes, edges or colours in an image.
Once the computer is trained, then they are used on new raw or untested data to check the precision and accuracy of the algorithm. The results improve gradually when the system is exposed to a large amount of data.
Furthermore, a deep learning technique is used to train the artificial neural networks of computer vision to identify and categorize the data by recognizing various features and patterns, just like the human brain.
What is the working principle of computer vision?
Computer vision’s main working principle is to make a computer program that works and responds exactly like the human brain would respond after viewing an image or a video. Thus, to achieve this, computer vision works with the help of two main components, and they are as follows:
1. A sensory device: Camera, is one such example of sensory devices as such it captures the images and videos in real time.
2. An interpreting device: A computer that interprets the data that are transmitted from a sensory device and make a trend, pattern or extract the meaning of the image or video.
Computer vision divides the image into various small pixels and assigns them numerical digits that represent categories like brightness, edges, patterns, and color grading for computers to process them easily. This is done by dividing the image into small grids, also known as pixels.
Once the data is converted into the language the computer understands, then a machine learning technique is used to identify the pattern, trends, and features like shape, edges, color, or the meaning of the image content. For instance, IBM used computer vision to make their famous “My Moments” feature that showcases a few important events that are captured within a specific period of time and showcases in a format of a reel or a short video. This helps the user to track down their important moments and revisit their old memories via a short video which was curated specially for them.
Applications of Computer Vision:
Computer vision is used in various sectors due to its amazing capabilities to perform time-consuming and tedious tasks that tend to be laborious for humans. The applications are as follows:
1. Machine inspection: Computer vision can be used to examine and evaluate the condition, quality, and expected life expectancy of the product or components of the machine.
2. 3D modeling: 3D modelling is one of the most used application as such it enables the user to create various products as per the requirement and do the research on the design with very less money. Through this, they can make many upgradation on the model that the user is making at home without any hassle.
3. Optical character recognition: Optical character recognition provides an ability to identify and scan the texts from the scanned documents and images.
4. Retail: Automatic checkout system, customer tracking, and inventory management system are some of the most frequently used application of the computer vision.
5. Medical imaging: X-rays, and CT scans can be used for the treatment and diagnosis of the patient with the help of computer vision as such it will be able to analyze the medical images more accurately.
6. Automotive safety: This feature in yet another amazing attribute of computer vision, as such it can be used as a driver assistance system and self driving vehicles to detect and react according to the obstacles that come infront of them in order to avoid collision.
7. Surveillance: Surveillance sector has gained alot of advancement after the usage of computer vision as such it can scan and detect faces of the person that are on lookout in the real time without any error and efficiently.
8. Biometrics and fingerprint recognition: Nowadays many companies have opted for biometrics and fingerprints recognition for their day to day attendance or for the verification as such it provides a hassle free experience for both the parties (employer and employee).
9. Motion capture: In the animation sector, motion capture is used to capture the movement of the actors in order to inculcate them into the characters of the animation movies or for virtual reality content.
10. Match move: It is used in the movies, as such it merges and aligns CGI elements seamlessly with the live action footage for better cinematic experience which would have been quite difficult to perform without the help of computer vision.
Conclusion
Computer vision is a field that deals with many difficulties that need to be taken into consideration for the betterment and upgrading of the system. To cite a few, data limitation, hardware requirement, and learning rate are some of the main aspects that one should focus on for the improvement of the field.
Although there are many corners where computer vision need improvement and will improve in the near future. Thus it is safe to say that if anyone wants to make their future career in this sector then they must as such it definitely looks promising.
