DCT-Based Videoprinting on Saliency-Consistent Regions for Detecting Video Copies with Text Insertion

  • Rong Yang
  • Yonghong Tian
  • Tiejun Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5879)


Ideal video fingerprinting should be robust to various practical distortions. Conventional fingerprinting mainly copes with natural distortions (brightness change, resolution reduction, etc.), while always gives poor performance in case of text insertion. One alterative way is to apply a weighting scheme based on the probability of text insertion for feature similarity calculation. However, the weights must be learned with labeled samples. In this paper, we propose a method that first addresses valid regions where the saliency values keep consistent between the query and original frames, namely saliency-consistent regions. Other regions, probably the inserted ones, are discarded. Then a DCT-based hamming distance is calculated on those saliency-consistent regions. Besides, the saliency-based distance is also considered and a further weighted linear distance is evaluated. The proposed algorithm is tested on the MPEG-7 video fingerprint dataset, achieving a false rate of 0.7% in case of text insertion and 0.32% in average for other 8 distortions.


Text insertion saliency-consistent region saliency map discrete cosine transform (DCT) video copy detection 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rong Yang
    • 1
  • Yonghong Tian
    • 2
  • Tiejun Huang
    • 2
  1. 1.Graduate University of Chinese Academy of SciencesBeijingChina
  2. 2.National Engineering Laboratory for Video TechnologyPeking UniversityBeijingChina

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