This study proposes a robust video hashing for video copy detection.The proposed method,which is based on representative-dispersive frames(R-D frames),can reveal the global and local information of a video.In this method,a video is represented as a graph with frames as vertices.A similarity measure is proposed to calculate the weights between edges.To select R-D frames,the adjacency matrix of the generated graph is constructed,and the adjacency number of each vertex is calculated,and then some vertices that represent the R-D frames of the video are selected.To reveal the temporal and spatial information of the video,all R-D frames are scanned to constitute an image called video tomography image,the fourth-order cumulant of which is calculated to generate a hash sequence that can inherently describe the corresponding video.Experimental results show that the proposed video hashing is resistant to geometric attacks on frames and channel impairments on transmission.