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Efficient Computation of Intensity Profiles for Real-Time Vision

  • Ernst Dieter Dickmanns
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1998)

Abstract

For the EMS-vision system realized on distributed general- purpose processors with a set of video cameras on an active gaze control platform, an efficient method for exploiting area-based image information has been developed (as opposed to edge features preferred in real- time vision systems up to now). It relies on the same oriented intensity gradient operators as have been used for edge localization in the past (K(C)RONOS). However, the goal achieved now is fast derivation of one-dimensional intensity profiles with piecewise linear shading models. First, regions of large intensity changes (so-called ‘non-homogeneous’ regions) are separated from ‘homogeneous’ ones containing at most moderate intensity changes (to be specified by a threshold parameter). The average intensity values and ternary mask responses in these areas yield information for a coarse linear (first order) intensity model. Then, in the homogeneous regions, the one-dimensional equivalent of a pyramid (a triangle-) representation is derived for the residues between the actual intensity values and the coarse linear model. Depending on the size of the homogeneous region and the number of intensity peaks, a certain triangle level for further processing is selected. Again, a (different) ternary mask operator is used for intensity gradient computation and for finding the zero-crossings of the gradient. This information is sufficient for determining the fine structure of regions with linear shading models. Examples are given for road and vehicle detection and recognition.

Keywords

Intensity Gradient Vehicle Detection Zero Crossing Object Hypothesis Coarse Segmentation 
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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References

  1. 1.
    P. J. Burt, T. H. Hong, A.Rosenfeld: Segmentation and estimation of image region properties through cooperative hierarchical computation. IEEE Trans. Syst. Man and Cybern. 12 (1981) 802–805.CrossRefGoogle Scholar
  2. 2.
    Dickmanns, Dirk: Rahmensystem für visuelle Wahrnehmung veränderlicher Szenen durch Computer. Dissertation, UniBwM, Informatik,(1997).Google Scholar
  3. 3.
    E. D. Dickmanns, V. Graefe: a) Dynamic monocular machine vision. b) Application of dynamic monocular machine vision. J. Machine Vision Application, Springer-Int, (1988) 223–261.Google Scholar
  4. 4.
    E. D. Dickmanns and H.-J. Wünsche: Dynamic vision for Perception and Control of Motion. In Jaehne(ed.): Handbook of Computer Vision and Applications, Vol.3: Systems and Applications Academic Press (1999) 569–620.Google Scholar
  5. 5.
    R. Gregor, M. Lützeler, M. Pellkofer, K.H. Siedersberger, E.D. Dickmanns: EMS Vision: A Perceptual System for Autonomous Vehicles. Proc. Int. Symposium on Intelligent Vehicles (IV’2000), Dearborn, (MI), October 4–5, 2000.Google Scholar
  6. 6.
    K.-D. Kuhnert: Zur Echtzeit-Bildfolgenanalyse mit Vorwissen. Dissertation UniBw Munich, LRT, (1988).Google Scholar
  7. 7.
    B. Mysliwetz: Parallelrechner-basierte Bildfolgen-Interpretation zur autonomen Fahrzeugsteuerung. Dissertation UniBw Munich, LRT, (10.8.1990).Google Scholar
  8. 8.
    F. R. Schell: Bordautonomer automatischer Landeanflug aufgrund bildhafter und inertialer Messdatenauswertung. Dissertation UniBw Munich, LRT, (23.3.1992).Google Scholar
  9. 9.
    S. Werner: MaschinelleWahrnehmung für den bordautonomen automatischen Hubschrauberflug. Dissertation, UniBw Munich, LRT, (17.7.1997).Google Scholar
  10. 10.
    H.-J. Wuensche: Erfassung und Steuerung von Bewegungen durch Rechnersehen. UniBw Munich LRT (1987).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Ernst Dieter Dickmanns
    • 1
  1. 1.UniBw Munich, Institut fuer Systemdynamik und FlugmechanikNeubibergGermany

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