Video halftoning is a key technology for use in electronic paper (e-paper) or smart paper, which is an emerging display device that has received considerable attention recently. In this paper, a temporal frequency of flickering-distortion optimized video halftoning method is proposed. We first uncover three visual defects that conventional neighboring frame referencing-based video halftoning methods, due to their sequential changes of reference frames, will encounter. To deal with the problem, we then propose a reference frame update per GOP-based error diffusion video halftoning method based on a flickering sensitivity-based human visual model. To efficiently compromise between average temporal frequency of flickering (ATFoF) and visual quality, temporal frequency of flickering-distortion (TFoFD) is presented as a metric for video halftoning performance evaluation. Based on the proposed probability model of video halftoning, the TFoFD curve can be accurately estimated to optimize the tradeoff between quality and ATFoF before the video is halftoned. Our temporal frequency of flickering-distortion optimization strategy can also be applied to other video halftoning schemes for performance improvement. Experimental results and comparisons with known methods demonstrate the effectiveness of our video halftoning method.