Computer vision is the field of artificial intelligence that focuses on enabling computers to understand and analyze visual data, such as images and video. It involves using machine learning and computer vision algorithms to analyze and interpret visual data, and to extract information and meaning from it.
Computer vision has a wide range of applications, including object recognition, facial recognition, image and video analysis, and more. It is used in many fields, including healthcare, finance, manufacturing, and security, to enable computers to make decisions based on visual data.
There are several steps involved in computer vision:
Image acquisition: This involves capturing and storing visual data, such as images or video, in a suitable format for analysis.
Preprocessing: This involves cleaning and preparing the data for analysis, such as by removing noise, correcting distortions, and adjusting the lighting.
Feature extraction: This involves extracting important features from the data, such as edges, patterns, and shapes, that can be used to recognize and classify objects.
Classification: This involves using machine learning algorithms to classify the data based on the extracted features.
Detection and tracking: This involves using algorithms to detect and track objects in the data, such as faces or vehicles.
Scene understanding: This involves using algorithms to analyze and interpret the data to understand the context and meaning of the visual data.
Computer vision is a powerful tool for enabling computers to understand and analyze visual data, and it has a wide range of applications in many fields.