Real-time textured object recognition on distributed systems

  • J. You
  • W. P. Zhu
  • H. A. Cohen
  • E. Pissaloux
Session IA1b — Feature Matching & Detection
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)


This paper presents the development of a real-time system for recognition of textured objects. In contrast to current approaches which mostly rely on specialized multiprocessor architectures for fast processing, we use a distributed network architecture to support parallelism and attain real-time performance. In this paper, a new approach to linage matching is proposed as the basis of object localization and positioning, which involves dynamic texture feature extraction and hierarchical image matching. A mask based stochastic method is introduced to extract feature points for matching. Our experimental results demonstrate that the combination of texture feature extraction and interesting point detection provides a better solution to the search of the best matching between two textured images. Furthermore, such an algorithm is implemented on a low cost heterogeneous PVM (Parallel Virtual Machine) network to speed up the processing without specific hardware requirements.

Key words

object recognition image matching feature extraction interesting points distance transform parallel processing distributed systems 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • J. You
    • 1
  • W. P. Zhu
    • 1
  • H. A. Cohen
    • 2
  • E. Pissaloux
    • 3
  1. 1.School of Computer and Information SciencesUniversity of South AustraliaThe LevelsAustralia
  2. 2.Department of Computer Science and Computer EngineeringLa Trobc UniversityBundooraAustralia
  3. 3.Institut d'Electronique FondamentaleUniversité Paris XIOrsay, CedexFrance

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