Automatic video diagnosing method using embedded crypto-watermarks
This paper proposes a novel automatic video diagnosing method. The purpose of this study is to detect the attack added on the authorized video and identify the attack category. The video is added with the crypto-watermarks using dual-domain quaternary watermarking algorithm in advance. The crypto-watermarks, which are generated using visual cryptography, have different capabilities against the various attacks. We extract the watermarks from the suspected video, measure the bit-error-rate between the extracted and specified crypto-watermarks, and then analyze bit-error-rates to determine what kind of attack added on the video. The experimental results demonstrate that the proposed method not only can identify the single attack, but it can identify the composite attack and detect the corrupted frames. Even if the video is not embedded with crypto-watermarks, we can differentiate it from the authorized videos.