Fingerprinting schemes use digital watermarks to determine originators of unauthorized/pirated copies. Multiple users may collude and collectively escape identification by creating an average or median of their individually watermarked copies. We present a scalable codebook generation scheme to increase the number of fingerprinted users. We extended the ACC (anti-collusion code) scheme using a Gaussian distributed random variable for medium attack robustness. We experimented with our scheme using human visual system based watermarking scheme, and the simulation results with standard test images show good collusion detection performance over average and median collusion attacks.