Finding interesting stellar structures inside large astronomical datasets is a challenging task. Depending on the type of data different techniques are needed to tackle this challenge. In this paper, we focus on the GAIA survey DR1, which provides the sky positions and G-band magnitudes for more than 109 stars. We compare the use of the magnitude distribution (or luminosity function) and Difference of Gaussian filtering extracted from small patches of the sky to detect globular clusters (GC). By using a Nearest Neighbor Retrieval strategy we find windows which depict similar magnitude distribution or filter responses compared to the ones extracted from known GCs. Our first results show that the Difference of Gaussian filters are advantageous to find spherical structures such as GC if only limited information, such as sky position and G-band magnitudes, are available.
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