Camera interface
Program camera functions yourself with the Vision standard
When users want to run functions they have created themselves on intelligent cameras, they encounter two challenges: On the one hand, they often only have access to proprietary interfaces, which makes it more difficult to process the data in third-party applications, and on the other hand, only a few models offer a high-speed data interface such as GigE Vision.
However, industrial applications often require both. IDS therefore combines standard vision industrial cameras with the vision app-based IDS NXT concept. Thanks to the "Smart GenICam App", data generated by customer-specific programming can be used in exactly the same way as if it were part of the manufacturer-independent standard functional scope of the industrial camera.
As a camera interface, GenICam enables standardized camera functions on the one hand, while on the other, camera manufacturers can integrate special functions using the feature node map (the camera API, so to speak). IDS is currently developing a "Smart GenICam" vision app with which customers can also integrate and use their own camera features in a vision-compliant manner. The function should be available from the second quarter of 2019.
Users load the new camera function onto their IDS NXT camera packaged as a vision app. The camera firmware then integrates the application code into the range of functions. The configuration, control and results of the Vision App can be easily processed in any GenICam-compliant third-party application, such as Halcon, via the camera's XML description file - while simultaneously utilizing the full GigE bandwidth.
The use of vision-compliant applications on the IDS NXT platform offers a further advantage, as application processes can be scaled between the camera and host PC. As powerful embedded systems, models such as IDS NXT rio and rome offer the possibility of shifting decision-making processes from the host PC partially or completely to the camera ("on the edge"). Advantages include a lower network load, hardware-accelerated processing, lower energy consumption and lower system costs. as
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