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Removing an Object from Video Sequence Algorithm Implemented on Analog CNN and DSP Microprocessors

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Artificial Neural Networks – ICANN 2010 (ICANN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6352))

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Abstract

CNN Universal Machine which contains Digital Signal Processor (DSP) in addition to ACE16k which is the hardware verification of Cellular Neural Networks are used increasingly in image processing applications with their advanced computational features. In this study, an removing an object from video sequence algorithm on a Bi-i Cellular Vision System which is a CNN Universal Machine was applied and the running times of both processors were evaluated.

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Author information

Authors and Affiliations

  1. Research and Application Center for Computer Sciences, Istanbul University, Istanbul, Turkey

    Emel ARSLAN

  2. Department of Computer Engineering, Istanbul University, Istanbul, Turkey

    Sabri ARIK

Authors
  1. Emel ARSLAN
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  2. Sabri ARIK
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Editor information

Editors and Affiliations

  1. Department of Informatics, TEI of Thessaloniki, 57400, Sindos, Greece

    Konstantinos Diamantaras

  2. School of Physics, Astronomy, and Informatics, Department of Informatics, Nicolaus Copernicus University, ul. Grudziadzka 5, 87-100, Torun, Poland

    Wlodek Duch

  3. Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, Pantazidou 193, 68200, Orestiada, Thrace, Greece

    Lazaros S. Iliadis

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© 2010 Springer-Verlag Berlin Heidelberg

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ARSLAN, E., ARIK, S. (2010). Removing an Object from Video Sequence Algorithm Implemented on Analog CNN and DSP Microprocessors. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15819-3_75

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  • DOI: https://doi.org/10.1007/978-3-642-15819-3_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15818-6

  • Online ISBN: 978-3-642-15819-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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