Digital Video Fingerprinting via Macroblock Coefficient Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital video fingerprinting techniques face challenges in robustness and efficiency, particularly when dealing with transcoding, resampling, and editing, and require significant processing resources, especially for modern compression standards like H.264.
Innovation Solution
The method generates digital video fingerprints by analyzing quantized transform coefficients of macroblocks, using a threshold criterion to select residual macroblocks, and forming test values based on these coefficients, allowing for robust and efficient fingerprinting in the DCT domain without full pixel decoding, and comparing fingerprints across different encoding processes and standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel-based fingerprinting is used to achieve reliable video identification, then measurement precision is improved, but device complexity and processing requirements increase significantly
Solution Approach 1:
The video content is divided into multiple macroblocks, and fingerprints are extracted from selected macroblocks rather than processing the entire video at pixel level. This segmentation allows reliable identification while reducing overall processing complexity.
Solution Approach 2:
The invention extracts only the necessary fingerprint information from selected macroblocks rather than processing all pixel data. By taking out only the essential features needed for identification, the system achieves reliable fingerprinting with reduced computational burden.
2Measurement precision
If full decoding to pixel level is performed to extract fingerprints, then measurement precision is improved, but productivity decreases due to high processing requirements
Solution Approach 1:
The system performs partial decoding only to the macroblock level and selects specific macroblocks for fingerprint extraction, rather than fully decoding to pixel level. This partial action provides sufficient accuracy for reliable identification while dramatically improving processing efficiency.
3Reliability
If traditional watermarking is applied to identify video content, then reliability is improved, but ease of operation worsens due to vulnerability to unlocking and tampering
Solution Approach 1:
Instead of embedding watermarks that can be removed, the system extracts inherent fingerprint features directly from the video content's macroblocks. These extracted fingerprints are inherently tied to the content and cannot be easily removed without significantly altering the video, thus improving security resistance while maintaining identification reliability.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A digitally encoded video fingerprinting system for generating and comparing/matching fingerprints from digitally encoded video which has been encoded according to an encoding method which involves the generation of residual macroblocks of pixels and the generation of quantized transform coefficients of the residual macroblocks, or of portions of the residual macroblocks, comprises a fingerprint database (5) and a video processing subsystem (10). The video processing subsystem (10) includes a fingerprint sequence selection module (14, 24) which is operable to select one or more sets of frames from input video content to be processed in order to generate a fingerprint; a fingerprint calculation module (14, 26) which is operable to generate a fingerprint based on a set of frames selected by the fingerprint sequence selection module; and a fingerprint comparator module (14, 28) which is operable to compare two fingerprints and to output a similarity score of the compared fingerprints. The method used by the fingerprint selection and fingerprint calculation modules includes selecting a group of frames of the encoded video content; processing the digitally encoded video content to obtain a set of quantized transform coefficients of residual macroblocks or portions of residual macroblocks associated with each of the selected frames; identifying a set of residual macroblocks per frame whose transform coefficients satisfy a threshold criterion; and generating a digital video fingerprint for the encoded video content in dependence upon the identified macroblocks or some property thereof within each of the selected frames.