Segmentation Algorithm via Cellular Neural/Nonlinear Network: Implementation on Bio-Inspired Hardware Platform Public Deposited

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  • Karabiber, Fethullah
    • Affiliation: College of Arts and Sciences, Department of Chemistry
  • Abstract The Bio-inspired (Bi-i) Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.
Date of publication
  • doi:10.1186/1687-6180-2011-69
Resource type
  • Article
Rights statement
  • In Copyright
Rights holder
  • Fethullah Karabiber et al.; licensee BioMed Central Ltd.
Journal title
  • EURASIP Journal on Advances in Signal Processing
Journal volume
  • 2011
Journal issue
  • 1
Page start
  • 69
  • English
Is the article or chapter peer-reviewed?
  • Yes
  • 1687-6180
Bibliographic citation
  • EURASIP Journal on Advances in Signal Processing. 2011 Sep 21;2011(1):69
  • Open Access
  • Springer

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