Investigating solar cycles using mathematical morphology

In this study, we report on the processing and analysis of around 9700 images of the solar disk, obtained from the SOHO and SDO satellites, available in the Helioviewer database. Using our own code, PyMoST (Python Morphological Sunspot Tracker), which employs a mathematical morphology technique, we were able to automatically track and analyze approximately 50000 sunspots in these images, covering the period from January 1, 1998 to July 31, 2024. By using PyMoST we were able to obtain the distribution of the number of spots as a function of solar latitude and time, accurately reproducing solar cycles 23, 24 and the current phase of solar cycle 25, in agreement with the literature. In addition, our code was also able to determine the areas and number of sunspots, showing excellent correlation with the results reported by the Royal Greenwich Observatory (RGO), Kodaikanal Solar Observatory (KSO) and the International Sunspot Number - Solar Influences Data Analysis Center (SIDIC), thus consolidating the efficiency of our tool and its importance for the investigation of solar magnetic activity.