In order to prevent illegal video copies, many video fingerprints have been developed. Video fingerprints should be robust from various video transformations and have high discriminative powers. In general, video fingerprints are generated from three feature spaces such as luminance, gradient, and DCT coefficients. However, there is a few study for the robustness and discrimination according to feature spaces. Thus, we analyzed the property of each feature space by video copy detion task with the robustness and the discrimination of video fingerprints. We generated three video fingerprints from these feature spaces using a same algorithm. In our test, a video fingerprint. based on DCT coefficient outperformed others because the discrimination of it was higher.