FPGA implementation of image processing technique for blood samples characterization

• A simple image processing technique based on etch detection with implementation capability on FPGA has been provided.
• A miniaturized system has been implemented for blood type determination for large number of samples.
• The implemented hardware is quit fast, low power with small size and has capability of embedding in handheld devices.

This work presents a hardware implementation of an image processing algorithm for blood type determination. The image processing technique proposed in this paper uses the appearance of agglutination to determine blood type by detecting edges and contrast within the agglutinated sample. 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 a Vertex 6 FPGA from Xilinx employing ISE software. Hardware implementation of the proposed algorithm on FPGA demonstrates a power consumption of 770 mW from a 2.5 V power supply. Blood type characterization using our FPGA implementation requires only 6.6 s, while a desktop computer-based algorithm with Matlab implementation on a Pentium 4 processor with a 3 GHz clock takes 90 s. The presented device is faster, more portable, less expensive, and consumes less power than conventional instruments. The proposed hardware solution achieved accuracy of 99.5% when tested with over 500 different blood samples.

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