Combining stereo and time-of-flight images with application to automatic plant phenotyping

  • Authors:

  • Yu Song;Chris A. Glasbey;Gerie W. A. M. van der Heijden;Gerrit Polder;J. Anja Dieleman

  • Affiliations:

  • Biomathematics and Statistics Scotland, The King's Buildings, Edinburgh, UK;Biomathematics and Statistics Scotland, The King's Buildings, Edinburgh, UK;Biometris, Wageningen UR, AC Wageningen, Netherlands;Biometris, Wageningen UR, AC Wageningen, Netherlands;Wageningen UR Greenhouse Horticulture, Wageningen, Netherlands

  • Venue:
  • SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
  • Year:
  • 2011

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Abstract

This paper shows how stereo and Time-of-Flight (ToF) images can be combined to estimate dense depth maps in order to automate plant phenotyping. We focus on some challenging plant images captured in a glasshouse environment, and show that even the state-of-the-art stereo methods produce unsatisfactory results. By developing a geometric approach which transforms depth information in a ToF image to a localised search range for dense stereo, a global optimisation strategy is adopted for producing smooth and discontinuity-preserving results. Since pixel-by-pixel depth data are unavailable for our images and many other applications, a quantitative method accounting for the surface smoothness and the edge sharpness to evaluate estimation results is proposed. We compare our method with and without ToF against other state-of-the-art stereo methods, and demonstrate that combining stereo and ToF images gives superior results.