SunBurst: a software for automated detection and measurement of solar prominences from solar drawings

The recovery and quantitative analysis of historical solar observations is of increasing interest to the Earth and space physics community. In this work, we present the development and validation of an open-source software tool designed to automatically detect and measure solar prominences in scanned hand-drawn solar disk images. The images belong to the Strach Collection, a unique set of observations recorded between 1969 and 2008 by Dr. Eric H. Strach. Our algorithm, implemented in Python using OpenCV and NumPy libraries, identifies red ink markings representing prominences around a detected solar disk, and measures key geometric parameters such as angular position, surface area, maximum height, and base width. The methodology combines color space transformations, morphological operations, contour analysis, and polar coordinate transformation. We validate our tool using several synthetic and real datasets and compare its measurements with those from historical catalogs such as the Coimbra Astronomical Observatory. The software, dataset, and methodology presented here contribute to the ongoing effort to digitally preserve and scientifically exploit historical solar records.