Most conventional features used in speaker authentication are based on estimation of spectral envelopes in one way or another, e.g., Mel-scale Filterbank Cepstrum Coefficients (MFCCs), Linear-scale Filterbank Cepstrum Coefficients (LFCCs) and Relative Spectral Perceptual Linear Prediction (RASTA-PLP). In this study, Spectral Subband Centroids (SSCs) are examined. These features are the centroid frequency in each subband. They have properties similar to formant frequencies but are limited to a given subband. Empirical experiments carried out on the NIST2001 database using SSCs, MFCCs, LFCCs and their combinations by concatenation suggest that SSCs are somewhat more robust compared to conventional MFCC and LFCC features as well as being partially complementary.