Object Detection Using Unit-Linking PCNN Image Icons

  • Xiaodong Gu
  • Yuanyuan Wang
  • Liming Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


A new approach to object detection using image icons based on Unit-linking PCNN (Pulse Coupled Neural Network) is introduced in this paper. Unit-linking PCNN, which has been developed from PCNN exhibiting synchronous pulse bursts in cat and monkey visual cortexes, is a kind of time-space-coding SNN (Spiking Neural Network). We have used Unit-linking PCNN to produce the global image icons with translation and rotation invariance. Unit-linking PCNN image icon (namely global image icons) is the 1-dimentional time series, and is a kind of image feature extracted from the time information that Unit-linking PCNN code the 2-dimentional image into. Its translation and rotation invariance is a good property in object detection. In addition to translation, rotation invariance, the object detection approach in this paper is also independent of scale variation.


Test Image Object Detection Rotation Invariance Pulse Couple Neural Network Spike Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaodong Gu
    • 1
  • Yuanyuan Wang
    • 1
  • Liming Zhang
    • 1
  1. 1.Department of Electronic EngineeringFudan UniversityShanghaiP.R. China

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