How do you think the new GigE standards will influence the machine vision industry?
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Autonomous applications can represent some of the most extreme environments, given the absence of human personnel as part of the image-capturing process. Heat, vibration and altitude for example—pushed to greater levels without restrictions of an actual person as part of the system—can impact imaging systems onboard unmanned aerial vehicles scanning seas, mountains and deserts for weapons and enemy troops. Depending on the application, images may initiate some course of autonomous action or may be transmitted to a central system where additional personnel evaluate, interpret and share information in real-time.
In a surgical setting, real-time imaging is directly integrated with medical procedures. Not autonomous at all, systems must withstand uniquely demanding conditions and deliver high-quality images to surgeons and other medical personnel making immediate decisions about patient care. Imaging systems are connected to a medical device such as an endoscope; for example, a doctor may or may not take a biopsy based on what information the imaging portion of the device is providing. The computing platform in this instance also controls the entire system, including the actions of the camera and the medical tools attached to the camera.
The more images and data doctors can evaluate while examining a patient, the better patient care they can provide. In medical imaging devices such as X-ray, ultrasound and MRI machines, the need for extremely high-resolution images that can be manipulated quickly has driven medical equipment developers to require better graphics, faster processing and speedy communication capabilities. Some imaging applications can still be handled off-line with batch processing, however many treatments require patient images in real time. And the need for processing power does not end there, as image processing and analysis is inherently tied to patient screening and diagnostics.
Requirements for real-time imaging include pattern recognition, organ rendering, volumetric analysis, multiple image type comparisons, and the ability to process related information from databases. Bringing these tasks to remote military or mobile outpatient facilities is also increasing demand, frequently meaning the same high level of compute power must be designed into smaller and smaller devices.
For designers working in extreme imaging systems, the building blocks have never been stronger or more varied. Compact, future-safe and power efficient components are rugged enough today to meet high-end computational demands under environmental extremes—and these standards-compliant offerings are evolving still, and will soon go even further in handling the harshest of imaging environments. AI