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Solar plages, which are bright regions on the Sun's surface, are an importantindicator of solar activity. In this study, we propose an automated algorithmfor identifying solar plages in Ca K wavelength solar data obtained from theKodaikanal Solar Observatory. The algorithm successfully annotates all visuallyidentifiable plages in an image and outputs the corresponding calculated plageindex. We perform a time series analysis of the plage index (rolling mean)across multiple solar cycles to test the algorithm's reliability androbustness. The results show a strong correlation between the calculated plageindex and those reported in a previous study. The correlation coefficientsobtained for all the solar cycles are higher than 0.90, indicating thereliability of the model. We also suggest that adjusting the hyperparametersappropriately for a specific image using our web-based app can increase themodel's efficiency. The algorithm has been deployed on the Streamlit CommunityCloud platform, where users can upload images and customize the hyperparametersfor desired results. The input data used in this study is freely available fromthe KSO data archive, and the code and the generated data are publiclyavailable on our GitHub repository. Our proposed algorithm provides anefficient and reliable method for identifying solar plages, which can aid thestudy of solar activity and its impact on the Earth's climate, technology, andspace weather.

An Image Processing approach to identify solar plages observed at 393.37 nm by the Kodaikanal Solar Observatory