Location of Repository

Modelling and analysis of plant image data for crop growth monitoring in horticulture

By Yu Song

Abstract

Plants can be characterised by a range of attributes, and measuring these attributes accurately and reliably is a major challenge for the horticulture industry. The measurement of those plant characteristics that are most relevant to a grower has previously been tackled almost exclusively by a combination of manual measurement and visual inspection. The purpose of this work is to propose an automated image analysis approach in order to provide an objective measure of plant attributes to remove subjective factors from assessment and to reduce labour requirements in the glasshouse. This thesis describes a stereopsis approach for estimating plant height, since height information cannot be easily determined from a single image. The stereopsis algorithm proposed in this thesis is efficient in terms of the running time, and is more accurate when compared with other algorithms.\ud The estimated geometry, together with colour information from the image, are then used to build a statistical plant surface model, which represents all the information from the visible spectrum. A self-organising map approach can be adopted to model plant surface attributes, but the model can be improved by using a probabilistic model such as a mixture model formulated in a Bayesian framework. Details of both methods are discussed in this thesis.\ud A Kalman filter is developed to track the plant model over time, extending the model to the time dimension, which enables smoothing of the noisy measurements to produce a development trend for a crop. The outcome of this work could lead to a number of potentially important applications in horticulture

Topics: QA76, SB
OAI identifier: oai:wrap.warwick.ac.uk:2032

Suggested articles

Preview

Citations

  1. (1996). 3-D computer vision using structured light: Design, calibration, and implementation issues. doi
  2. (1996). 3-d computer vision using structured light. doi
  3. (2000). A cautionary note on likelihood ratio tests in mixture models. doi
  4. (2003). A class of discrete multiresolution random fields and its application to image segmentation. doi
  5. (2000). A mcmc approach to hierarchical mixture modelling.
  6. (1988). A multi-resolution, probabilistic approach to 2D inverse conductivity problems. doi
  7. (1989). A multiresolution stereopsis algorithm based on the gabor representation.
  8. (1960). A new approach to linear filtering and prediction problems. doi
  9. (1974). A new look at the statistical model identification. doi
  10. (1998). A pixel dissimilarity measure that is insensitive to image sampling. doi
  11. (2005). A quasi-dense approach to surface reconstruction from uncalibrated images. doi
  12. (1985). A stochastic analysis of a modified gain extended kalman filter with applications to estimation with bearings only measurements. doi
  13. (2004). A survey of point-based techniques in computer graphics. doi
  14. (2002). A taxonomy and evaluation of dense twoframe stereo correspondence algorithms. doi
  15. (2006). A visual vocabulary for flower classifi-cation. doi
  16. (1999). An Introduction to Support Vector Machines: And Other Kernel-based Learning Methods. doi
  17. (1995). An introduction to the Kalman filter.
  18. Assistant Secretary of Defense for Public Affairs. The pentagon: Facts & figures.
  19. (2001). Automated monitoring of greenhouse crops. doi
  20. (2005). Automated rose cutting in greenhouses with 3D vision and robotics: Analysis of 3D vision techniques for stem detection. Acta Horticulturae,
  21. (2008). Bayes’ theorem. In doi
  22. (2005). Bayesian hierarchical clustering. doi
  23. (1994). Bayesian model choice: Asymptotics and exact calculations.
  24. (2007). Bayesian surface estimation from multiple cameras using a prior based on the visual hull and its application to image based rendering. doi
  25. Camera calibration toolbox for Matlab. doi
  26. (2000). Chrysanthemum stunt viroid. Department for Environment, Food and Rural Affairs,
  27. (2001). Color features for quality control in ceramic tile industry. doi
  28. (2003). Comparison of graph cuts with belief propagation for stereo, using identical mrf parameters. doi
  29. (1990). Competitive learning algorithms for vector quantization. doi
  30. (1985). Computational experiments with a feature-based stereo algorithm. doi
  31. (1992). Computer and Robot Vision, doi
  32. (1982). Computer Vision. doi
  33. (1992). Control of plant height in poinsettia by temperature drop and graphical tracking. Acta Horticulturae, 327:41–48,
  34. (1976). Cooperative computation of stereo disparity. doi
  35. (1980). De pictura. In doi
  36. (2007). Delving into the whorl of flower segmentation. doi
  37. (1999). Discrete-Time Signal Processing. Prentice Hall, 2nd edition,
  38. (2002). Does colorspace transformation make any difference on skin detection? doi
  39. (1995). Dynamic cell structure learns perfectly topology preserving map. doi
  40. (2006). Efficient belief propagation for early vision. doi
  41. (1978). Estimating the dimension of a model. doi
  42. (1990). Estimating uncertain spatial relationships in robotics. doi
  43. Estimation of finite mixture distributions through bayesian sampling.
  44. (2007). Evaluation of cost functions for stereo matching. doi
  45. (1964). Extrapolation, Interpolation, and Smoothing of Stationary Time Series. doi
  46. Fast stereo matching using rectangular subregioning and 3D maximum-surface techniques. doi
  47. (2000). Finite Mixture Models. doi
  48. (1989). Forecasting, structural time series models and the Kalman filter. doi
  49. (2007). Global Positioning Systems, Inertial Navigation, and Integration. doi
  50. (2004). Graphical tracking systems revisited: A practical approach to computer scheduling in horticulture.
  51. (2003). Handbook of Fingerprint Recognition. doi
  52. (1998). Hierarchical control of small autonomous helicopters. doi
  53. (1995). Image analysis for the biological sciences. doi
  54. (1997). Image analysis: a tool for assessing plant uniformity and variety matching.
  55. (2006). Image-based plant modeling. doi
  56. (2007). Image-based tree modeling. doi
  57. (1995). Imaging as a technique for assessment and control in the field.
  58. (2005). Intelligent distributed surveillance systems: a review. doi
  59. (1997). Introduction to Random Signals and Applied Kalman Filtering. doi
  60. (1989). Kalman filter-based algorithms for estimating depth from image sequences. doi
  61. (2007). Knowledge and heuristic-based modeling of laser-scanned trees. doi
  62. (2008). Local stereo matching with adaptive support-weight, rank transform and disparity calibration. doi
  63. (1991). Machine vision: automated visual inspection and robot vision. doi
  64. (1977). Maximum likelihood from incomplete data via the em algorithm.
  65. (1993). Mesh optimization. doi
  66. MGMM: Multiresolution Gaussian Mixture Models for computer vision. doi
  67. (1996). Mixtures of distributions: Inference and estimation.
  68. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. doi
  69. (2006). Modeling plant structures using concept sketches. doi
  70. (1997). Modelling uncertainty in agricultural image analysis. doi
  71. (2004). Monte Carlo Statistical Methods. doi
  72. (1997). Moore’s law: past, present and future. doi
  73. (2002). Multi-camera scene reconstruction via graph cuts. doi
  74. (1992). Multiresolution estimation of 2-d disparity using a frequency domain approach. doi
  75. (1988). Multiresolution image modelling and estimation. doi
  76. (1994). Multiscale recursive estimation, data fusion, and regularization. doi
  77. (2003). Multivariate Bayesian Statistics: Models for Source Separation and Signal Unmixing. doi
  78. (1992). Numerical recipes in C, doi
  79. (1951). On information and sufficiency. doi
  80. (2002). Os. An autonomous robot for harvesting cucumbers in greenhouses. doi
  81. (2005). Photoconsistency and multiresolution methods for light field disparity estimation.
  82. (1996). Progressive meshes. doi
  83. (2006). Putting plant growth in the picture - image analysis for computer assisted grading and crop tracking.
  84. (1984). Pyramid methods in image processing.
  85. (1998). Quality models in horticulture need product quality: A rare but challenging field of exploration. Acta Horticulturae,
  86. (1998). Recent progress in coded structured light as a technique to solve the correspondence problem: a survey. doi
  87. (1998). Refining initial points for k-means clustering.
  88. (1994). Representing moving images with layers. Image Processing, doi
  89. Robust phase correlation. doi
  90. (1990). Sampling-based approaches to calculating marginal densities. doi
  91. (1996). SCAAT: Incremental Tracking with Incomplete Information. doi
  92. (1990). Self-organizing hierarchical feature maps. doi
  93. (2001). Self-organizing map as a probability density model. doi
  94. (1997). Self-organizing maps. Springer-Verlag, 3rd edition, doi
  95. (1986). Signal Processing: The model-based approach. doi
  96. (2000). Single view metrology. doi
  97. (2002). Statistical color models with application to skin detection. doi
  98. (1985). Statistical decision theory and Bayesian analysis. doi
  99. (2000). Statistical pattern recognition: A review. doi
  100. (1985). Stereo by intra- and inter-scanline search using dynamic programming. doi
  101. (2006). Stereo matching via learning multiple experts behaviors. doi
  102. (2009). Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling. doi
  103. (1989). Stereoscopic depth: its relation to image segmentation, grouping, and the recognition of occluded objects. doi
  104. (1970). Stochastic Processes and Filtering Theory. doi
  105. (1990). Structural image codebooks and the selforganizing feature map algorithm. doi
  106. (2007). Surface modelling of plants from stereo images. doi
  107. (1999). Surface reconstruction from unorganized points using selforganizing neural networks.
  108. (1989). The fast computation of disparity from phase differences. doi
  109. (2000). The infinite Gaussian mixture model.
  110. (1996). The Kalman filter in finance. doi
  111. (1983). The Laplacian pyramid as a compact image code. doi
  112. (2007). The measurement and improvement of robust bedding plant quality and the use of digital imaging for quality assessment.
  113. (1975). The phase correlation image alignment method.
  114. (2001). The statistical analysis of plant part appearance – a review. Computers and Electronics in Agriculture, doi
  115. (2004). Thermal and chlorophyll-fluorescence imaging distinguish plant-pathogen interactions at an early stage. doi
  116. (2001). Time Series Analysis by State Space Methods. doi
  117. (1990). Time Series Analysis, Forecasting and Control. Holden-Day, Incorporated, doi
  118. (1997). Today’s thermal imaging systems: background and applications for civilian law enforcement and military force protection. doi
  119. (1995). Towards the optimal bayes classifier using an extended selforganising map.
  120. (2007). Ultra high-resolution 3D laser color imaging of paintings: The mona lisa by leonardo da vinci. doi
  121. (2002). Virtualizing a Byzantine crypt by combining high-resolution textures with laser scanner 3D data. doi
  122. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. doi
  123. (1994). Winner-take-all networks for physiological models of competitive learning. doi
  124. (2005). Wireless Communications & Networks. doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.