Abstract
This paper proposes a method to visualize different regions into image of biospeckle patterns using Self-Organizing Maps. Images are obtained from sequences of laser speckle images of biological specimens. The dynamic speckle is a phenomenon that occurs when a beam of coherent light illuminates a sample in which there is some type of activity, not visible, which results in a variable pattern over time. Self-Organizing Maps have shown an efficient behavior for the identification of regions according to the activity of the phenomenon involved. In this paper we show results obtained in the segmentation of regions in corn seeds, particularly the detection of the floury zone.
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Passoni, L.I. et al. (2013). Improvements in the Visualization of Segmented Areas of Patterns of Dynamic Laser Speckle. In: Estévez, P., Príncipe, J., Zegers, P. (eds) Advances in Self-Organizing Maps. Advances in Intelligent Systems and Computing, vol 198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35230-0_17
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DOI: https://doi.org/10.1007/978-3-642-35230-0_17
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