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A mixed-signal VLSI circuit for skeletonization by grassfire transformation

  • Part VIII: Implementations
  • Conference paper
  • First Online:
Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

This paper presents a novel mixed-signal VLSI focal-plane array processor performing the morphological operation of skeletonization of binary images at a processing speed of up to IOK frames/second. The chip directly implements the grassfire algorithm. The system is a 2D array of identical processing elements (PEs) with integrated photodetectors allowing parallel optical input. The skeleton computation is performed in a fully parallel, asynchronous manner by local interactions between PEs, the transformed image is represented by analog values. The transformation is a VLSI analogue of time-integrated off-center-on-surround type nonlinear computation. The output of the transformation can be serially accessed with an on-chip raster-scan circuit generating multiscanning-compatible video signal. The system is currently being physically designed in a standard 0.7µm digital CMOS process. Layout of the processing element and preliminary system specifications are presented.

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Author information

Authors and Affiliations

  1. Institute of Isotopes, Hung. Acad. Sci., P.O.B. 77, H-1525, Budapest, Hungary

    M. Oláh & A. Lőrincz

  2. CSEM, Neuchâtel, 71, CH-2007, Maladière, Switzerland

    M. Oláh

  3. Dept. of Electron Devices, TUB, H-1521, Budapest, Hungary

    P. Masa

Authors
  1. M. Oláh
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  2. P. Masa
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  3. A. Lőrincz
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Oláh, M., Masa, P., Lőrincz, A. (1997). A mixed-signal VLSI circuit for skeletonization by grassfire transformation. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020315

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  • DOI: https://doi.org/10.1007/BFb0020315

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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