In this paper, we propose a simple and fast method for chord recognition in music signals. We extract a chromagram from the signal which transcribes the harmonic content of the piece over time. We introduce a set of chord templates taking into account one or more harmonics of the pitch notes of the chord and calculate a scale parameter to fit the chromagram frames to these chords templates. Several chord types (major, minor, dominant seventh, etc.) are considered. The detected chord over a frame is the one minimizing a measure of fit between the rescaled chroma vector and the chord templates. Several popular distances and divergences from the signal processing or probability fields are considered for our task. Our system is improved by some post-processing filtering that modifies the recognition criteria so as to favor time-persistence. The transcription tool is evaluated on three corpora: the Beatles corpus used for MIREX 08, a 20-audio-song corpus, and a resynthesized MIDI corpus. Our system is also compared to state-of-the-art chord recognition methods. Experimental results show that our method compares favorably to the state-of-the-art and is less computationally demanding than the other evaluated systems. Our systems entered the MIREX 2009 competition and performed very well.