Pełnotekstowe zasoby PLDML oraz innych baz dziedzinowych są już dostępne w nowej Bibliotece Nauki.
Zapraszamy na


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2009 | 19 | 4 | 679-689

Tytuł artykułu

An automatic segmentation method for scanned images of wheat root systems with dark discolourations

Treść / Zawartość

Warianty tytułu

Języki publikacji



The analysis of plant root system images plays an important role in the diagnosis of plant health state, the detection of possible diseases and growth distortions. This paper describes an initial stage of automatic analysis-the segmentation method for scanned images of Ni-treated wheat roots from hydroponic culture. The main roots of a wheat fibrous system are placed separately in the scanner view area on a high chroma background (blue or red). The first stage of the method includes the transformation of a scanned RGB image into the HCI (Hue-Chroma-Intensity) colour space and then local thresholding of the chroma component to extract a binary root image. Possible chromatic discolourations, different from background colour, are added to the roots from blue or red chroma subcomponent images after thresholding. At the second stage, dark discolourations are extracted by local fuzzy c-means clustering of an HCI intensity image within the binary root mask. Fuzzy clustering is applied in local windows around the series of sample points on roots medial axes (skeleton). The performance of the proposed method is compared with hand-labelled segmentation for a series of several root systems.








Opis fizyczny




  • Computer Engineering Department, Technical University of Łódź, Stefanowskiego 18/22, 90-924 Łódź, Poland
  • Computer Engineering Department, Technical University of Łódź, Stefanowskiego 18/22, 90-924 Łódź, Poland
  • Department of Plant Physiology and Biochemistry, University of Łódź, Banacha 12/16, 90-237 Łódź, Poland
  • Department of Plant Physiology and Biochemistry, University of Łódź, Banacha 12/16, 90-237 Łódź, Poland


  • Bernsen, J.(1986). Dynamic thresholding of grey-level images, Proceedings of the 8th International Conference on Pattern Recognition, Paris, France, pp. 1251-1255.
  • Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, NY.
  • Glasbey, C. A. and Horgan, G. W. (1995). Image Analysis for the Biological Sciences, John Wiley & Sons, Inc., New York, NY.
  • Gonzalez, E. R., Woods, R. E. and Eddins S. L. (2004). Digital Image Processing Using MATLAB, Prentice Hall, Upper Saddle River, NJ.
  • Gonzalez, R. C. and Woods, R. C. (2008). Digital Image Processing, Prentice Hall, Upper Saddle River, NJ.
  • Hasthorpe, J, and Mount, N. (2007). The generation of river channel skeletons from binary images using raster thinning algorithms,
  • Horvath, J. (2006). Image segmentation using fuzzy c-means,
  • Jung, V., Olsson, E., Caspersen, S., Asp, H., Jensen, P. and Alsanius, B. W. (2004). Response of young hydroponically grown tomato plants to phenolic acids, Scientia Horticulturae 100(1-4): 23-37.
  • Lam, L., Lee, S-W. and Suen, C. Y. (1992). Thinning methodologies-A comprehensive survey, IEEE Transactions on Pattern Analysis and Machine Intelligence 14(9): 869-885.
  • Lambert, P. and Carron, T. (1999). Symbolic fusion of luminance-hue-chroma features for region segmentation, Pattern Recognition 32(11):1857-1872.
  • Mohamed, N. A., Ahmed, M. N. and Farag A. (1999). Modified fuzzy c-means in medical image segmentation, Proceeding of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Phoenix, AZ, USA, Vol. 6, pp. 3429-3432.
  • Nord, E. (2008). Other Uses for WinRhizo,
  • Otsu, N. (1979). A threshold selection method from grey-level histograms, IEEE Transactions on Systems, Man, and Cybernetics 9(1): 62-66.
  • Regent Instruments Inc. (2008). WinRHIZO For root morphology and architecture measurement,
  • Seregin, I. V. and Kozhevnikova, A. D. (2009). Enhancement of nickel and lead accumulation and their toxic growthinhibitory effects on amaranth seedlings in the presence of calcium, Russian Journal of Plant Physiology 56(1): 80-84.
  • Serra, J., (1986). Introduction to mathematical morphology, Computer Vision, Graphics and Image Processing 35(3): 283-305.
  • Smit, L. A., Bengough, A. G.,Engels, C., Van Noordwijk, M., Pellerin, S. and Van de Geijn, S. C. (2000). Root Methods: A Handbook, Springer Verlag, Heidelberg.
  • Terry N., Zayed A.M., de Souza M.P. and Tarun A.S. (2000). Selenium in higher plants, Annual Review of Plant Physiology and Plant Molecular Biology 51: 401-432.
  • The Mathworks Inc. (2008a). Image Processing Toolbox User's Guide,
  • The Mathworks Inc. (2008b). Fuzzy Logic Toolbox User's Guide,
  • Vincent, L. and Soille, P. (1991). Watersheds in digital spaces: An efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence 13(6): 583-598.
  • Zobel, R. W., Kinraide, T. B. and Baligar, V.C. (2007). Fine root diameters can change in response to changes in nutrient concentration, Plant and Soil 297(1-2): 243-254.

Typ dokumentu



Identyfikator YADDA

JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.