Committee Machine for Road-Signs Classification

  • Bogusław Cyganek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)


The paper presents a system for the road signs recognition which is based on an ensemble of the non Euclidean distance neural networks and an arbitration unit. The input to this system constitutes a binary pictogram of a sign which is supplied from the detection module. The classifier is composed of a mixture of experts – the Hamming neural networks – each working with a single group of deformed reference pictograms. The ensemble of experts is controlled by an arbitration module operating in the winner-takes-all mode. Additionally it is equipped with a promoting mechanism that favours the most populated group of unanimous experts. The presented classifier is characterized by the fast training and very fast response times which features make it suitable for the driving assistant systems. The presented concepts have been verified experimentally. Their results and conclusions are also discussed.


Input Pattern Road Sign Driving Assistant System Winning Neuron Binary Distance 
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

  • Bogusław Cyganek
    • 1
  1. 1.AGH – University of Science and TechnologyKrakówPoland

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