Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran
Today, great observatories around the world, devote a substantial amount of observing time to sky surveys. The resulted images are inputs of source finder modules. These modules search for the target objects and provide us with source catalogues. We sought to quantify the ability of detection tools in recovering faint galaxies regularly encountered in deep surveys. Our approach was based on completeness estimation in magnitude - size plane. The adopted method was incorporating artificial galaxies. We improvised a software that estimates completeness in a given interval of magnitude and size. The software generates artificial galaxies and iteratively inserts them to the source finder modules input image. Evaluating the ratio of the number of detected to the number of inserted artificial galaxies provides us with means to estimate completeness. Completeness estimation is helpful in selecting unbiased samples.