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Efficient Hardware Architectures and Algorithms for Embedded Vision Systems

Abstract : Abstract : In this talk we develop three main axes i) design of efficient hardware architectures, ii) computational efficient algorithms targeted for embedded vision systems and iii) hardware support for self-aware computing. We will introduce recent advances within the unifying framework of mathematical morphology. We propose a first morphological processor with arbitrarily large neighborhoods. It allows to obtain previously unachieved performances for serially composed morphological filters, geodesical and conditional operators. The cited processor is based on a novel algorithm formulation of morphological dilation. Finally, the applicative domain will be illustrated in scene understanding context for self aware embedded computing.
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Contributor : Eva Dokladalova Connect in order to contact the contributor
Submitted on : Monday, February 1, 2016 - 4:11:55 PM
Last modification on : Saturday, January 15, 2022 - 3:56:04 AM



  • HAL Id : hal-01263835, version 1



Eva Dokladalova. Efficient Hardware Architectures and Algorithms for Embedded Vision Systems. 2015. ⟨hal-01263835⟩



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