A connectivity-based method for detecting clumpy structures in molecular clouds

Abstract

The structure of molecular clouds plays a vital role in star formation. Therefore, automatic and accurate detection of molecular clumps is one of the foundations of large-scale sky survey analysis. We present a molecular clump detection method based on morphology, gradient, and a merging rule. The image morphology processing is employed to extract the signal regions, while gradient-ascending analysis is utilized for segmenting signal regions into local regions. Then, a connectivity-based merging rule related to the physical properties of the local regions is used to merge them into individual clumps, and each individual clump has connectivity of topology. The proposed method yields good performance for crowded simulated clumps at different SNR levels. The method has also experimented on the observational and synthetic data, and a high recall rate of 88.6% can achieve.