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    • Thesis & Design Report, BSc (Electrical and Electronic Engineering)
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    •   BracU IR
    • BSRM School of Engineering
    • Department of Electrical and Electronic Engineering (EEE)
    • Thesis & Design Report, BSc (Electrical and Electronic Engineering)
    • View Item
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    Design and VLSI implementation of high performance face recognition system

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    Thesis Paper.pdf (2.993Mb)
    Date
    2013-04
    Publisher
    BRAC University
    Author
    Dewan, Priyanka Das
    Shamma, Tasnim Harun
    Abbas, Afifa
    Mondol, Raktim Kumar
    Metadata
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    URI
    http://hdl.handle.net/10361/2503
    Abstract
    In this paper, we have proposed a novel hardware architecture for face-recognition system. In order to make the system cost effective we have used a simple yet efficient algorithm of face-recognition system. We have designed, implemented and verified the algorithm in a cyclone III Field Programmable Gate Array (FPGA) chip. Altera DE0 development board which contains a cyclone III chip on it have been used for debugging purpose. We have also ensured for low power consumption such that the chip could be used universally in a wide range of security systems. To develop a simple yet efficient face recognition algorithm (such as PCA, FFT etc.) on digital hardware, we have researched on various face recognition algorithms using Matlab codes and studied their detection efficiency under various posture and background and also the complexity of the algorithm. To save hardware resource and at the same time to obtain an acceptable level of recognition we have chosen to use Fast Fourier Transform. The search database is developed by taking pictures of BRAC University students in various background and postures and used them to evaluate the developed face recognition system. Images were captured using TRDB_D5M camera module and digital data from the camera was transferred to the SDRAM of the DE0 board using GPIO interface. A NIOS2 microprocessor was synthesized in the cyclone III chip which controlled the total recognition system and the communication between the FFT core, SDRAM and On-chip memory. The performance of the hardware is now under evaluation.
    Keywords
    FFT; FPGA; FAce Recognition; Nios2; TRDB_D5M; Electrical and electronic engineering
     
    Description
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2013.
     
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 86-87).
    Department
    Department of Electrical and Electronic Engineering, BRAC University
    Type
    Thesis
    Collections
    • Thesis & Design Report, BSc (Electrical and Electronic Engineering)

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