A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Finding Interesting Associations without Support Pruning
IEEE Transactions on Knowledge and Data Engineering
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Feature Extraction and a Database Strategy for Video Fingerprinting
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
New Iterative Geometric Methods for Robust Perceptual Image Hashing
DRM '01 Revised Papers from the ACM CCS-8 Workshop on Security and Privacy in Digital Rights Management
Scalable near identical image and shot detection
Proceedings of the 6th ACM international conference on Image and video retrieval
Spatio–Temporal Transform Based Video Hashing
IEEE Transactions on Multimedia
Modeling and analysis of content identification
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Random Gray code and its performance analysis for image hashing
Signal Processing
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Content identification has many applications, ranging from preventing illegal sharing of copyrighted content on video sharing websites, to automatic identification and tagging of content. Several content identification techniques based on watermarking or robust hashes have been proposed in the literature, but they have mostly been evaluated through experiments. This paper analyzes binary hash-based content identification schemes under a decision theoretic framework and presents a lower bound on the length of the hash required to correctly identify multimedia content that may have undergone modifications. A practical scheme for content identification is evaluated under the proposed framework. The results obtained through experiments agree very well with the performance suggested by the theoretical analysis.