Object detection using unit-linking PCNN image icons

Authors:
Xiaodong Gu;Yuanyuan Wang;Liming Zhang
Affiliations:
Department of Electronic Engineering, Fudan University, Shanghai, P.R. China;Department of Electronic Engineering, Fudan University, Shanghai, P.R. China;Department of Electronic Engineering, Fudan University, Shanghai, P.R. China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

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.