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

Calliope-Louisa Sotiropoulou [et.al.] - Nama Orang;

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 (corresponding to approx. 60 ). 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.
Index Terms—Field-programmable gate array (FPGA), flow detection, Lab-on-Chip, machine vision, microfluidic, monitoring.


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Informasi Detail
Judul Seri
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
No. Panggil
-
Penerbit
New York : IEEE., 2014
Deskripsi Fisik
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, VOL. 8, NO. 2, APRIL 2014
Bahasa
English
ISBN/ISSN
1932-4545
Klasifikasi
-
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
VOL. 8, NO. 2, APRIL 2014
Subjek
TEKNIK
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Yuli/Agus
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  • FULL TEXT. Real-Time Machine Vision FPGA Implementation for Microfluidic Monitoring on Lab-on-Chips
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