FOCAS Automatic Catalog Matching Algorithms

This paper describes efficient algorithms that automatically take two or more catalogs of objects with instrumental coordinates and magnitudes and matches them. The challenges are that the instrumental coordinates may be only partially overlapping, at a different scale, rotated, or even inverted (flipped). The object magnitudes may be derived from different passbands so that the relative magnitudes of the objects differ. Also, the catalog may not contain all the same objects due to differences in separating close objects or to partial overlap between images. Finally, the catalog positions and magnitudes are subject to noise in the images from which they were derived. The algorithms are applicable to any automated cataloging system. However, the implementation described here is part of the Faint Object Classification and Analysis System (FOCAS). FOCAS automatically produces catalogs of objects from digital images. The algorithms described here first take a subsample of the brightest obj...