• Prof. Tejal Deshpande
• Stella J

Blood grouping is the first and foremost essentiality for many of the major medical procedures. Microscopy has intermittently proved inefficient since it is time consuming ,the results are difficult to reproduce and also there is a need of an expert. Traditional ways of detecting blood group have remained analogue in this era of digitization and are therefore susceptible to human fallibility. Due to these reasons, automation of evaluation process is of high importance. It would be very efficient and arguably a lifesaving approach if the process of detecting blood can be completed successfully in a cost- effective way with the technologies at hand and without the plausibility of man-made error. This proposition is expected to evaluate the group of a sample blood with its computed image. The whole process excludes a major probability of human error while detecting the agglutination from the traditional method and it would get the task done within a fairly insignificant amount of time. An FPGA implementation and parallel processing algorithms are used in conjugation with image processing techniques to make this system reliable for the characterization of large numbers of blood samples. The program was developed using Matlab software then transferred and implemented on Arty 7000 Zync FPGA from Xilinx employing Vivado software. FPGA’s have the advantages of speed and re-configurability which is required for image processing applications. Hardware implementation of the proposed algorithm on FPGA demonstrates a power consumption of 890 mW from a 2.5 V power supply. Blood group characterization using our FPGA implementation requires only 5.6 s, while a desktop computer-based algorithm with Matlab implementation on a Intel core i5 processor with 8 GB RAM and 1.60 GHz clock takes 120 s. The presented device is faster, more portable, less expensive, and consumes less power than conventional instruments. The proposed hardware solution achieved accuracy of 99% when tested with over 100 different blood samples.

ABO system, Agglutination, Blood samples, BRAM , Camera, Canny edge, Image Processing.

"FPGA Based Blood sample Characterization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.807-813, June 2019, Available :http://www.jetir.org/papers/JETIR1908120.pdf

"FPGA Based Blood sample Characterization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp807-813, June 2019, Available at : http://www.jetir.org/papers/JETIR1908120.pdf