Processing laser scanner plant data to extract structural information

Hanan, Jim and Loch, Birgit and McAleer, Tim (2004) Processing laser scanner plant data to extract structural information. In: 4th International Workshop on Functional-Structural Plant Models (FSPM 2004), 7-11 Jun 2004, Montpellier, France.

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Plant architecture information has traditionally used the hierarchical structure of the plant as its basis, with digitised point data from real plants entered in a particular hierarchical pattern. Data collection and classification have thus been inseparable. The advent of laser profile scanners, such as the Polhemus FastSCAN, means that 3D plant data can be captured holistically. The data acquired from laser surface scanners is in unordered point cloud form, with points collected only on the surface of the object under study. This means that the structure of the plant must be extracted from the cloud of 3D coordinates using manual methods. This paper describes issues arising when using a Polhemus FastSCAN laser scanner, and a program for manual extraction of points developed at the Advanced Computational Modelling Centre (ACMC), which can be used independently or with specialised software such as FloraDig.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: No evidence of copyright restrictions.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 24 May 2008 10:53
Last Modified: 10 Oct 2013 23:43
Uncontrolled Keywords: laser scanners; 3D models
Fields of Research : 06 Biological Sciences > 0607 Plant Biology > 060705 Plant Physiology
01 Mathematical Sciences > 0199 Other Mathematical Sciences > 019999 Mathematical Sciences not elsewhere classified
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences

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