FPGA-based machine vision implementation for Lab-on-Chip flow detection

This paper presents an FPGA-based machine vision implementation for flow detection on Lab-on-Chip (LoC) experiments. The proposed machine vision system is designed to provide real-time information to the LoC user about the state of the flows (flow coordinates and points of interest) as well as input...

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Bibliographic Details
Published in2012 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 2047 - 2050
Main Authors Sotiropoulou, C-L, Voudouris, L., Gentsos, C., Nikolaidis, S., Vassiliadis, N., Demiris, A., Blionas, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Field programmable gate arrays
Image edge detection
Machine vision
Microfluidics
Noise
Real time systems
Streaming media
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Summary:This paper presents an FPGA-based machine vision implementation for flow detection on Lab-on-Chip (LoC) experiments. The proposed machine vision system is designed to provide real-time information to the LoC user about the state of the flows (flow coordinates and points of interest) as well as input to the LoC controller. It is uniquely designed to compensate noise in the input video originating from non ideal lighting conditions or LoC movement. This machine vision implementation achieves real time response for input videos of 1Mpixel resolution and frame-rates exceeding 60fps for microfluidic flows with a maximum speed of 20mm/sec.
ISBN:9781467302180
146730218X
ISSN:0271-4302
2158-1525
DOI:10.1109/ISCAS.2012.6271683