Polyphonic transcription needs a correct identification of notes and chords. We have centered the efforts in piano chords identification. Pattern recognition using spectral patterns has been used as the identification method. The spectrum of the signal is compared with a set of spectra (patterns). The patterns are generated by a piano model that takes into account acoustic parameters and typical manufacturer criteria, that are adjusted by training the model with a few notes. The algorithm identifies notes and, iteratively, chords. Chords identification requires spectral substraction that is performed using masks. The analyzing algorithm used for training, avoids false partials detection due to nonlinear components and takes into account inharmonicity for spectrum segmentation. The method has been tested with live piano sounds recorded from two different grand pianos. Successful identification of up to four-notes chords has been carried out.