Hierarchical image analysis using irregular tessellations

  • Annick Montanvert
  • Peter Meer
  • Azriel Rosenfeld
Image Features

DOI: 10.1007/BFb0014847

Volume 427 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Montanvert A., Meer P., Rosenfeld A. (1990) Hierarchical image analysis using irregular tessellations. In: Faugeras O. (eds) Computer Vision — ECCV 90. ECCV 1990. Lecture Notes in Computer Science, vol 427. Springer, Berlin, Heidelberg

Abstract

In this paper we have presented an image analysis technique in which a separate hierarchy is built over every compact object of the input. The approach is made possible by a stochastic decimation algorithm which adapts the structure of the hierarchy to the analyzed image. For labeled images the final description is unique. For gray level images the classes are defined by converging local processes and slight differences may appear. At the apex every root can recover information about the represented object in logirhtmic number of processing steps, and thus the adjacency graph can become the foundation for a reulational model of the scene.

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Copyright information

© Springer-Verlag 1990

Authors and Affiliations

  • Annick Montanvert
    • 1
  • Peter Meer
    • 2
  • Azriel Rosenfeld
    • 2
  1. 1.Equipe RFMQ - TIM3 (UA CNRS 397)Grenoble cedexFrance
  2. 2.Center for Automation ResearchUniversity of MarylandCollege ParkUSA