What is computer vision?
Computer vision is the field of artificial intelligence that focuses on programming the ability to understand and analyze visual information in the computer.
This field started developing in the 1960s when programmers developed algorithms to interpret and analyze visual data. But due to computational constraints, it was very limited. Then in the 1970s, people started developing algorithms for image and pattern recognition. Resultantly, the Hough transform algorithm was the first computer vision algorithm to be developed to detect lines and geometrical patterns. This began the era of computer vision which is still rapidly developing as a field.
Why do we need computer vision?
Computer vision today has various benefits. For one, it enables a machine to understand, interpret and analyze raw visual data into useful information. An example to understand its importance is by thinking about the human brain. Our brain receives countless amounts of data every millisecond, whether visual, sensory, or voice. It is fascinating to think about how our brain processes information from different senses simultaneously and provides us with exactly the information we need depending on how we want to see things. This is one of the goals of computer vision; to achieve a level that artificial intelligence can understand and interpret visual information for completing useful day-to-day tasks.
Another reason why computer vision is important is that it opens even broader windows in the field of artificial intelligence by providing advancements in other areas like robotics, bioinformatics and genomics, and many others. The field of computer vision has strengthened even more after developments in convolutional neural networks (CNNs) and deep learning.
Applications of computer vision
Following are the applications of computer vision:
Object recognition and image classification: The ability to distinguish an object from a provided environment helps in many everyday situations. Those objects can be categorized and used for autonomous vehicles, robotics, image search engines, e-commerce systems, medical imaging, security, and surveillance systems.
Lane and traffic detection: Computer vision helps detect and analyze traffic and lanes while tracking pedestrians to lessen road accidents and traffic jams.
Medical imaging: We can analyze medical images like MRI, X-rays, CT scans, ultrasounds, etc., using computer vision for faster diagnosis.
Surveillance: We can use computer vision to track suspicious behavior and people of interest and monitor crowds by using video surveillance cameras.
Facial recognition and biometrics: Computer vision can be used to identify people with their facial features, which helps in biometric authentication and security access.
Robotics: Computer vision is widely used in robotics to make them more human-friendly and interactive. It helps robots perceive the world in a way that helps them identify and grasp objects, navigate paths, and assist in factories and industries.
Gesture recognition: This computer vision application can be used for interpreting sign language and understanding gestures to increase human-computer interaction.
