Study On Rice Grain Recognition And Morphological Characteristics Based On NVST Observation

Solar granulation is a plasma convective phenomenon from the solar convection zone to the photosphere, which appear as a cellular pattern on the solar surface. Morphological characteristics and evolution process of granules can help us to better understand the mechanism of the convective motion and the relationship to solar magnetic field. Therefore, an accurate identification method is crucial to study the mechanism and relationship. However, the traditional identification methods based on intensity- and gradient- threshold are very difficult to identify granules because the intensity distribution of granules is non-uniform and their boundaries appear to be blurred. In this paper, we proposed a new method based on phase congruency to identify granules and analyzed their morphological characteristics.We selected two high-resolution image sequences taken from the New Vacuum Solar Telescope (NVST) at the Fuxian Solar Observatory (FSO) to illustrate the identification procedure. The identification procedure includes three steps:(1) obtaining phase congruency feature from an original image; (2) obtaining binary image of phase congruency feature; (3) morphological filter to extract granule shapes. For evaluating the accuracy of the proposed method, three traditional methods that based on intensity threshold, marked watershed and Laplace of Gaussian operator were compared to our method. Furthermore, we also selected three different thresholds to inspect the influence. The experiment result demonstrates that our proposed method is effective and accurate, and insensitive to those selected threshold.This demonstrates that our proposed method can be used to study granules evolution and their physical mechanism. Using the method, a total of 165694 and 108279 granules were identified from the first and the second data sets, respectively. The diameter of each granule was first obtained, and then their distributions were exhibited. We found that the distributions of Granules from the two data sets hold two obvious peaks, implying that the granules hold two different scales, and are called:mini granules whose diameters are smaller than 780 km and regular granules greater than 780 km. The four properties of the granules:diameter, mean intensity, ratio of long axis to short one, and fractal dimension were obtained from the two classes. From the statistical results from the identified granules, they are in good agreement with the previous conclusions, demonstrating that the method can be used to study granules evolution and their physical mechanism.