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Real-Time Machine Vision FPGA Implementation for Microfluidic Monitoring on Lab-on-Chips

机译:用于实时芯片实验室微流监控的实时机器视觉FPGA实现

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A machine vision implementation on a field-programmable gate array (FPGA) device for real-time microfluidic monitoring on Lab-On-Chips is presented in this paper. The machine vision system is designed to follow continuous or plug flows, for which the menisci of the fluids are always visible. The system discriminates between the front or “head” of the flow and the back or “tail” and is able to follow flows with a maximum speed of 20 mm/sec in circular channels of a diameter of 200 $mu{rm m}$ (corresponding to approx. 60 $mu {rm l}/{rm sec}$ ). It is designed to be part of a complete Point-of-Care system, which will be portable and operate in non-ideal laboratory conditions. Thus, it is able to cope with noise due to lighting conditions and small LoC displacements during the experiment execution. The machine vision system can be used for a variety of LoC devices, without the need for fiducial markers (such as redundancy patterns) for its operation. The underlying application requirements called for a complete hardware implementation. The architecture uses a variety of techniques to improve performance and minimize memory access requirements. The system input is 8 bit grayscale uncompressed video of up to 1 Mpixel resolution. The system uses an operating frequency of 170 Mhz and achieves a computational time of 13.97 ms (worst case), which leads to a throughput of 71.6 fps for 1 Mpixel video resolution.
机译:本文提出了一种在现场可编程门阵列(FPGA)设备上的机器视觉实现,用于对芯片实验室进行实时微流监控。机器视觉系统的设计遵循连续流动或活塞流动,对于这些流动,流体的弯液面始终可见。该系统在流的前部或“头部”与后部或“尾部”之间进行区分,并且能够在直径为200 $ mu {rm m} $的圆形通道中以最大20毫米/秒的速度跟随流(相当于大约60 $ mu {rm l} / {rm sec} $)。它被设计为完整的即时护理系统的一部分,该系统是便携式的,并且可以在非理想的实验室条件下运行。因此,它能够应对由于光照条件和实验执行过程中的小LoC位移引起的噪声。机器视觉系统可用于多种LoC设备,而无需对其进行操作的基准标记(例如冗余模式)。潜在的应用程序需求要求完整的硬件实现。该体系结构使用各种技术来提高性能并最小化内存访问要求。系统输入是分辨率高达1 Mpixel的8位灰度未压缩视频。该系统的工作频率为170 Mhz,计算时间为13.97 ms(最坏情况),对于1 Mpixel视频分辨率,其吞吐量为71.6 fps。

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