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Video copy detection is the process of detecting illegally copied videos by analyzing them and comparing them to original content. The goal of this process is to protect a video creator's intellectual property. == History == Indyk et al. produced a video copy detection theory based on the length of the film; however, it worked only for whole films without modifications. When applied to short clips of a video, Idynk et al.'s technique does not detect that the clip is a copy. Later, Oostveen et al. introduced the concept of a ''fingerprint'', or ''hash function'', that creates a unique signature of the video based on its contents. This fingerprint is based on the length of the video and the brightness, as determined by splitting it into a grid. The fingerprint cannot be used to recreate the original video because it describes only certain features of its respective video. Some time ago, B.Coskun et al. presented two robust algorithms based on discrete cosine transform. Hampapur and Balle created an algorithm creating a global description of a piece of video based on the video's motion, color, space, and length. To look at the color levels of the image was thought, and for this reason, Li et al. created an algorithm that examines the colors of a clip by creating a binary signature get from the histogram of every frame. This algorithm, however, returns inconsistent results in cases in which a logo is added to the video, because the insertion of the logo's color elements adds false information that can confuse the system. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Video copy detection」の詳細全文を読む スポンサード リンク
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