In this paper, a steganalysis technique using compression bit rate as a distinguishing statistic is presented to detect secret messages embedded in document images that are degraded in quality by printing, photocopying, and/or scanning processes. We consider embedding techniques that flip pixels in binary document images that contain characters and symbols. Noise introduced by printing, photocopying, and/or scanning can be modelled by a local optical distortion process. Steganographic embedding is modelled as an additive noise process and we use compression bit rate as a distinguishing statistic to discriminate between stego images and unmarked images. Experimental results showed that the proposed technique can detect stego images wtih reasonably good accuracy, given the inherent difficulty of the problem.