A new robust technique is presented for automated identification of sunspots on full-disk white-light (WL) solar images obtained from SOHO/MDI instrument and Ca II K1 line images from the Meudon Observatory. Edge-detection methods are applied to find sunspot candidates followed by local thresholding using statistical properties of the region around sunspots. Possible initial oversegmentation of images is remedied with a median filter. The features are smoothed by using morphological closing operations and filled by applying watershed, followed by dilation operator to define regions of interest containing sunspots. A number of physical and geometrical parameters of detected sunspot features are extracted and stored in a relational database along with umbra-penumbra information in the form of pixel run-length data within a bounding rectangle. The detection results reveal very good agreement with the manual synoptic maps and a very high correlation (96%) with those produced manually by NOAA Observatory, USA.
['Sergei I. Zharkov', 'Valentina V. Zharkova', 'Stanley S. Ipson', 'Ali K. Benkhalil']
Technique for automated recognition of sunspots on full-disk solar images