Audio or music fingerprints can be utilize to implement an economical music identification system on a million-song library, however the system needs great deal of memory to carry the fingerprints and indexes. Therefore, for a large-scale audio library, memory imposes a restriction on the speed of music identifications. So, we propose an efficient music identification system which used a kind of space-saving audio fingerprints. For saving space, original finger representations are sub-sample and only one quarters of the original data is reserved. In this approach, memory demand is far reduced and therefore the search speed is criticalincreasing whereas the lustiness and dependability ar well preserved. Mapping audio information to time and frequency domain for the classification, retrieval or identification tasks presents four principal challenges. The dimension of the input should be considerably reduced; the ensuing options should be strong to possible distortions of the input; the feature should be informative for the task at hand simple. We propose distortion free system which fulfils all four of these requirements. Extensive study has been done to compare our system with the already existing ones, and the results show that our system requires less memory, provides fast results and achieves comparable accuracy for a largescale database.