A dictionary-based approach for extracting repetitive patterns in music aiming at music feature extraction and indexing for audio database management is proposed. In this system, segmentation is achieved with the tempo information, and a music score is decomposed into bars. Each bar is indexed to construct a bar index table. Then, an adaptive dictionary-based compression algorithm known as Lempel Ziv 78 (LZ-78) is applied to the bar-represented music scores to extract repetitive patterns. Finally, pruning is applied to this dictionary to remove non-repeating patterns and to combine shorter repeating patterns into a longer one. The LZ78 algorithm is slightly modified to achieve better results in the current application context. Experiments performed on a popular music database of MIDI files demonstrated that the proposed algorithm extracts repeating melodies effectively with a speed of four times faster compared to the traditional linear search approach.