A Video Fingerprint Based on Visual Digest and Local Fingerprints

A fingerprinting design extracts discriminating features, called fingerprints. The extracted features are unique and specific to each image/video. The visual hash is usually a global fingerprinting technique with crypto-system constraints. In this paper, we propose an innovative video content identification process which combines a visual hash function and a local fingerprinting. Thanks to a visual hash function, we observe the video content variation and we detect key frames. A local image fingerprint technique characterizes the detected key frames. The set of local fingerprints for the whole video summarizes the video or fragments of the video. The video fingerprinting algorithm identifies an unknown video or a fragment of video within a video fingerprint database. It compares the local fingerprints of the candidate video with all local fingerprints of a database even if strong distortions are applied to an original content.