In the context of musical analysis, we propose an algorithm that automatically induces patterns from polyphonies. We define patterns as “perceptible repetitions in a musical piece”. The algorithm that measures the repetitions relies on some general perceptive notions: it is non-linear, non-symetric and non-transitive. The model can analyse any music of any genre that contains a beat. The analysis is performed into three stages. First, we quantize a MIDI sequence and we segment the music in “beat segments”. Then, we compute a similarity matrix from the segmented sequence. The measure of similarity relies on features such as rhythm, contour and pitch intervals. Last, a bottom-up approach is proposed for extracting patterns from the similarity matrix. The algorithm was tested on several pieces of music, and some examples will be presented in this paper.