Geintra

Departamento de electronica Universidad de Alcala

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    An Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis

    TítuloAn Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis
    Tipo de publicaciónJournal Article
    Año de publicación2010
    AutoresBravo, I, Mazo, M, Lazaro, JL, Gardel, A, Jiménez, P, Pizarro, D
    Idioma de publicaciónEnglish
    Revista académicaSensors
    Volumen10
    Número10
    Páginas9232-9251
    Fecha de publicación12/2010
    Rank in category11/56
    JCR CategoryInstruments & Instrumentation
    JCR Impact Factor1.870
    ISSN1424-8220
    URLhttp://www.mdpi.com/1424-8220/10/10/9232/
    DOI10.3390/s101009232
    Resumen

    This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices.