Image Processing Method for Epidermal Cells Detection and Measurement in Arabidopsis Thaliana Leaves

Arabidopsis thaliana is the most important model specie employed for genetic analysis in plants. As it has been extensively proven, the first pair of extended leaves and its cellular and morphological changes during Arabidopsis development, is and accurate model to understand the molecular and physiological events that control cell cycle progression in plants. Nevertheless, cell analysis on leaves depends significantly on images acquired from a microscopy coupled to a drawing tube, where cells are traced by hand for posterior digitalization and analysis. This process is tedious, inaccurate and highly temporally inefficient. A new image processing method for cell detection in leaves of Arabidopsis thaliana is presented. Using complementary image processing techniques, we introduce a good way to obtain the original cell contour shapes, surpassing the limitations given by factors like noise, stomata, blurred edges, and non-uniform illumination. Results show the new methodology minimizes considerably the time of cell detection compared with the microscopy coupled tube method, and produces matching percentages over 80%.