摘要： The variation of solar irradiance is one of the natural forcing mechanisms of the terrestrial climate. Hence, the time-dependent solar irradiance is an important input parameter for climate modelling. The solar surface magnetic field is a powerful proxy for solar irradiance reconstruction. The analyses of data obtained with the Michelson Doppler Imager (MDI) on board the SOHO mission are therefore useful for the identification of solar surface magnetic features to be used in solar irradiance reconstruction models. However, there is still a need for automated technologies that would enable the identification of solar activity features from large databases. To achieve this we present a series of enhanced segmentation algorithms developed to detect and calculate the area coverages of specific magnetic features from MDI intensitygrams and magnetograms. These algorithms are part of the Automated Solar Activity Prediction (ASAP) tool. The segmentation algorithms allow us to identify the areas on the solar disk covered by magnetic elements inside and outside boundaries of active regions. Depending on their contrast properties, magnetic features within an active region boundary are classified as sunspot umbra and penumbra, or faculae. Outside an active region boundary magnetic elements are identified as network. We present the detailed steps involved in the segmentation process and provide the area coverages of the segmented MDI intensitygrams and magnetograms. The feature segmentation was carried out on daily intensitygrams and magnetograms from April 21, 1996 to April 11, 2011. This offers an exciting opportunity to undertake further investigations that benefit from solar features segmentations, such as solar irradiance reconstruction, which we plan to investigate in the future.