09-03-2017, 03:02 PM
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding of digital images or videos. From an engineering perspective, it seeks to automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images and extracting high-dimensional data from the real world in order to produce numerical or symbolic information, for example, in decision-making. To understand in this context means the transformation of visual images (the entrance of the retina) into descriptions of the world that can interact with other thought processes and obtain the appropriate action. This understanding of the image can be seen as the unraveling of symbolic information from image data using models constructed with the help of geometry, physics, statistics and learning theory. As a scientific discipline, computer vision deals with the theory behind artificial systems that extract information from images. Image data can take many forms, such as video sequences, views from multiple cameras, or multidimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply its theories and models for the construction of computerized vision systems.
The applications of computer vision are numerous and include:
§ Agriculture
§ Augmented reality
§ Self-employed vehicles
§ Biometrics
§ character recognition
§ Forensic
§ industrial quality inspection
§ Facial recognition
§ gesture analysis
§ Geoscience
§ restoration of images
§ medical image analysis
§ pollution control
§ process control
§ remote sensing
§ Robotics
§ security and surveillance
§ transportation