Computer vision includes applications in medical, industrial, and military fields.
1, medical
The most prominent application area of medical is medical computer vision and medical image processing. This area features information extracted from image data for the purpose of making a medical diagnosis of the patient.
Usually, the image data is in the form of microscope images, X-ray images, angiography images, ultrasound images and tomography images, an example of information that can be extracted from such image data is the detection of tumors, atherosclerosis or other malignant changes. It can also be the dimensions of organs, blood flow, and so on.
This field of application also supports medical research by providing new information for the measurement of, for example, the structure of the brain, or about the quality of medical treatments. Applications of computer vision in the medical field also include the enhancement of images that are interpreted by humans, such as ultrasound images or X-ray images, to reduce the effect of noise.
2. Industrial
The second application area of computer vision is in industry, sometimes called machine vision, where information is extracted for the purpose of underpinning a manufacturing process.
One example is quality control, where information or end products are automatically detected in order to find defects. Another example is that of location and detail orientation measurements being picked up by a robot arm. Machine vision is also heavily used in agriculture for the process of optical sorting of food from bulk materials, a process known as removing the unwanted.
3. Military
Military applications are likely to be one of the largest areas for computer vision. The most obvious examples are detection of enemy soldiers or vehicles and missile guidance. More advanced systems for missile guidance send missiles to an area rather than a specific target, and when the missile reaches a target based on locally acquired image data in the area to make a selection.
Modern military concepts such as "battlefield awareness" imply that a variety of sensors, including image sensors, provide a wealth of information about operational scenarios that can be used to support strategic decision-making. In this case, automated processing of data is used to reduce complexity and fuse information from multiple sensors to improve reliability.