Image processing is widely growing as a useful tool in biosensing applications. It can be used to convert any camera/microscope into an optical sensor with wide range of capabilities such as monitoring completion of colorimetric reactions, differentiating and counting cells, and tracking motile cells/organisms. However, implementation of image processing in Lab-on-Chip devices is still challenging for researchers with little expertise in this field. Here, we present a multi-purpose real-time machine vision platform for tracking and analyzing objects inside lab-on-chip devices and for automating many microfluidic applications. Our LabVIEW-based machine vision platform, which is freely available on our webpage ( http://www.assiutmicrofluidics.com/research ), enables non-experts in image processing and machine vision to easily assemble their image processing pipeline based on the intended application. The program was designed for plug and play interfacing with a wide range of imaging devices including USB microscopes, high-speed cameras, and smartphone cameras. Moreover, to achieve portability, the program can be loaded on myRIO, a portable pocket size fully functional LabVIEW platform, to perform all program capabilities outside the lab without the need for a PC. To prove functionality of our program, we used it in real-time closed loop control of hydrodynamic focusing and control of flow velocity of cells inside a microchannel. We also demonstrated the program abilities in different lab-on-chip applications such as tracking, differentiation, and counting of blood cells.
Keywords: Cytometry; Image processing; Lab on chip; Machine vision; Microchannel; Microfluidics.