Comparison methods for object recognition

  • Authors:

  • Vladislav Skorpil;Jiri Stastny

  • Affiliations:

  • Department of Telecommunication, Institute of Automation and Computer Science, Brno University of Technology, Brno, Czech Republic;Department of Telecommunication, Institute of Automation and Computer Science, Brno University of Technology, Brno, Czech Republic

  • Venue:
  • ICS'09 Proceedings of the 13th WSEAS international conference on Systems
  • Year:
  • 2009

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Abstract

This paper describes our new unpublished results and outputs of selected methods for object recognition. It is continued to our former research. We are focused to the identification with the aid of moments, with the aid of syntactical analysis and with the aid of neural network algorithms. Momentum method is very sensitive to entry image quality. Syntactic analysis is suitable for rotated objects, high-speed classification and for small changes in the segment edge. Neural network algorithms can be used for high-speed classification with randomly rotated objects and for some differences between learned etalons and classified objects.