  Solar plages, which are bright regions on the Sun's surface, are an important
indicator of solar activity. In this study, we propose an automated algorithm
for identifying solar plages in Ca K wavelength solar data obtained from the
Kodaikanal Solar Observatory. The algorithm successfully annotates all visually
identifiable plages in an image and outputs the corresponding calculated plage
index. We perform a time series analysis of the plage index (rolling mean)
across multiple solar cycles to test the algorithm's reliability and
robustness. The results show a strong correlation between the calculated plage
index and those reported in a previous study. The correlation coefficients
obtained for all the solar cycles are higher than 0.90, indicating the
reliability of the model. We also suggest that adjusting the hyperparameters
appropriately for a specific image using our web-based app can increase the
model's efficiency. The algorithm has been deployed on the Streamlit Community
Cloud platform, where users can upload images and customize the hyperparameters
for desired results. The input data used in this study is freely available from
the KSO data archive, and the code and the generated data are publicly
available on our GitHub repository. Our proposed algorithm provides an
efficient and reliable method for identifying solar plages, which can aid the
study of solar activity and its impact on the Earth's climate, technology, and
space weather.
