Machine Vision

Performance, accuracy and energy efficiency are critical parameters for machine vision solutions at the edge. Edge computing solutions facilitate data processing near the source of data generation and serve as a decentralized extension of the cloud or data center networks. This eases the integration of machine vision with lower latency and reduces bandwidth by filtering the relevant data at the edge.

Machine Vision surrounds all industrial and non-industrial applications in which a combination of hardware and software provides operational guidance to devices in the execution of their functions, based on the capture and processing of images.

Machine Vision systems rely on digital sensors protected inside industrial cameras with specialized optics to acquire images so that computer hardware and software can process, analyze and measure various characteristics for decision making.

"Machine Vision improves quality and productivity, while driving down manufacturing costs! Machine Vision Process: Image Material IN / Useful Data OUT."
Jan Venema
CTO AimValley


Using Accelerated Edge Computing (AEC) benchmarking, profiling, and tuning tools we quickly identify performance bottlenecks in your existing applications. And migrate the key latency or bandwidth critical sections for hardware-assisted off-load to an FPGA accelerator card. 

Processing and throughput improvements by a factor of 5 or more are possible, depending on the algorithm; and power consumption can be reduced significantly when compared with graphics cards.

Compact FPGA-based controller for Factory 4.0



AimValley - Machine Vision - How can we help you?

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