Plant growth modelling from 2D images

Dr Jinhai Cai, Mr Ross FrickDr Mahmood Golzarian, Dr Hamid Laga and Professor Stan Miklavcic

The aim of this project is to automatically model the temporal plant growth patterns based on a sequence of images and to map the linkage between genotype and phenotype. The outcomes of this research program are becoming increasingly important given the establishment of advanced high throughput plant phenotyping facilities. The identification of plant growth stages is key to developing a plant growth stage ontology. It includes the recognition of plant leaves, stems, tillers, and spikes. Some plant components can be differentiated by temporal and spatial features. Therefore, it is essential to track the growth of the plant through its life. This research program will

  • develop image segmentation methods for plant images,
  • extract and analyse important features from the images,
  • design and implement pattern recognition methods to identify leaves, stems and spikes,
  • develop leaf tracking methods to distinguish leaves and tillers,
  • identify plant growth stages based on plant ontologies


J. CaiM.R. GolzarianS.J. Miklavcic (2011) Novel image segmentation based on machine learning and its application to plant analysis, Int. Journal of Information and Electronics Engineering, 1, 79-84.

J. CaiM.R. GolzarianS.J. Miklavcic, (2011) Novel image segmentation using Gaussian mixture models - application to plant phenotypic analysis, 3rd International Conference on Signal Acquisition and Processing (ICSAP), 308-312.

M.R. GolzarianJ. CaiR.A. FrickS.J. Miklavcic, (2011) Segmentation of cereal plant images using level set methods. A comparative study, Int. Journal of Information and Electronics Engineering, 1, 72-78.

M.R. Golzarian, J. Cai, R.A. Frick, S.J. Miklavcic (2011) A comparative evaluation of level set algorithms with applications for the segmentation of narrow-leaf plants", 3rd International Conference on Signal Acquisition and Processing (ICSAP), pp282-286.

M.R. GolzarianR.A. Frick, K. Rajendran, B. Berger, S. Roy, M. Tester, D.S. Lun. (2011) Accurate estimation of plant biomass using information extracted from high-throughput plant images, Journal of Plant Methods, 7(2), DOI: 10.1186/1746-4811-7-2.

Areas of study and research

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