Machine Vision and Applications

, Volume 21, Issue 6, pp 921–939 | Cite as

Estimating the motion of plant root cells from in vivo confocal laser scanning microscopy images

  • Timothy J. Roberts
  • Stephen J. McKenna
  • Cheng-Jin Du
  • Nathalie Wuyts
  • Tracy A. Valentine
  • A. Glyn Bengough
Original Paper


Images of cellular structures in growing plant roots acquired using confocal laser scanning microscopy have some unusual properties that make motion estimation challenging. These include multiple motions, non-Gaussian noise and large regions with little spatial structure. In this paper, a method for motion estimation is described that uses a robust multi-frame likelihood model and a technique for estimating uncertainty. An efficient region-based matching approach was used followed by a forward projection method. Over small timescales the dynamics are simple (approximately locally constant) and the change in appearance small. Therefore, a constant local velocity model is used and the MAP estimate of the joint probability over a set of frames is recovered. Occurrences of multiple modes in the posterior are detected, and in the case of a single dominant mode, motion is inferred using Laplace’e method. The method was applied to several Arabidopsis thaliana root growth sequences with varying levels of success. In addition, comparative results are given for three alternative motion estimation approaches, the Kanade–Lucas–Tomasi tracker, Black and Anandan’s robust smoothing method, and Markov random field based methods.


Motion estimation Plant root Living cell Confocal laser scanning microscopy Uncertainty 


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Timothy J. Roberts
    • 1
  • Stephen J. McKenna
    • 1
  • Cheng-Jin Du
    • 1
  • Nathalie Wuyts
    • 2
  • Tracy A. Valentine
    • 2
  • A. Glyn Bengough
    • 2
  1. 1.School of ComputingUniversity of DundeeDundeeScotland, UK
  2. 2.Scottish Crop Research InstituteDundeeScotland, UK

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