In this paper, an efficient spectrum sensing scheme to search the vacant frequency bands of desired bandwidth for green cognitive radios (GCRs) is proposed. The proposed scheme consists of low complexity reconfigurable fast filter bank (RFFB) followed by a bank of detectors and learning algorithm based on empirical observations. The RFFB allows high resolution control over subband bandwidth without hardware re-implementation. The simulation results show that the proposed N-subband RFFB based spectrum sensing scheme offers improved performance in terms of searching all the available vacant bands of desired bandwidth compared to N-subband uniform filter banks and other reconfigurable filter banks. The proposed scheme also offers improved performance in terms of searching the wide vacant bands which in turn protect the secondary (unlicensed) users against flat as well as frequency selecting fading. The complexity comparison indicates that total estimated gate count of the RFFB is substantially lower than other filter banks.