Up to the present, the majority of low contrast object evaluations performed on phantom images have been accomplished in a subjective fashion. This is mainly due to the time and effort required to manually measure each radiograph with a densitometer to obtain quantitative results. However, with the development of digital radiographic systems, it has become feasible to automate the detection and computation processes. In this work, a method that can automatically detect and compute the subject-to-noise ratio of the low contrast disks inside a geometric chest phantom is examined. This algorithm has the ability to locate the low contrast objects to an accuracy of less than one pixel, and provides results that are consistent with the understanding of subject-to-noise ratio. This algorithm should simplify the task of quantitative evaluation of contrast detail phantoms.