Computer vision, also known as technical vision, refers to the theory and technology focused on developing machines capable of detecting, recognizing, tracking, and classifying various objects using visual data. This field of study involves the creation of algorithms and systems that enable computers to interpret and understand visual information, similar to how humans perceive and process images.
Computer vision technology finds extensive applications in various systems and industries, including:
- Process control systems (such as industrial robots and self-driving cars) for automation and optimization of tasks.
- Video surveillance systems for monitoring and analyzing real-time video feeds for security and surveillance purposes.
- Information organization systems, where it aids in managing and indexing vast amounts of visual data in sound or image databases.
- Systems for modeling objects or environments, such as medical image analysis for diagnostics and treatment planning, and terrain map creation for navigation and mapping applications.
- Augmented reality systems, which overlay digital information on the real world to enhance user experiences in gaming, education, training, and more.
Overall, computer vision plays a crucial role in enabling machines to interpret visual data effectively, leading to advancements in automation, surveillance, information management, modeling, and augmented reality systems.