Processor memory capacity and update frequency are one of the main restricting constraints in star tracker design and development. In order to decrease the volume of the data required onboard, uniforming the star catalog which is eventually used as pattern recognition database is considered. Three different methods of uniforming the star catalog have been applied. Spherical patches, fixed slope curve and charged particles or Thomson’s problem. After generation of a sphere with uniform distribution of points, a star is assigned to each point according to its spherical distance or best magnitude. In order to evaluate the performance of each method, seven evaluation criteria are defined. Point distribution minimum energy, catalog size, minimum star required for pattern recognition, mean and standard deviation of star distribution in each frame, database size and pattern recognition true recognize percentage. These seven criteria are combined in weighted equation of “average” to choose the best star catalog uniforming method with respect to the star tracker mission. After having implemented the average equation it is demonstrated that uniforming the star catalog using charged particle or Thomson’s problem has better results.