A Mathematical Morphology Approach to the

We deal in this work with a broadly studied topic in astronomical imaging, namely the star#galaxy discrimination problem. Through the use of Mathematical Morphology,we propose an original approach to the characterization of these astronomical objects, which is based on gray-level shape-size information. The main steps in our method are image pre-processing, segmentation and feature extraction, all of which employ Mathematical Morphology tools that were implemented using the MMach toolbox for the Khoros system. We present a comparison between our segmentation results, based on the watershed method, and those of the SExtractor software package. The shapesize information is extracted through the use of the gray-level morphological pattern spectrum, which yields good analysis attributes that promise to be suitable for future work in neural-network automatic classi#cation