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Digital Video Copy Detection Using Steganography Frame Based Fusion Techniques

Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB,volume 30)


An effective and exact technique for copying video location in a huge dataset is the utilization of video pictures. We have exactly picked the shading format description, a minimal and powerful casing-based description to make pictures which are additionally determined by vector quantization (VQ). We recommend a new nonmetric length measure to discover the likeness among the question and a dataset video picture and tentatively demonstrate its better execution over other length measures for exact copy identification. The effective look cannot be executed for high-dimensional information utilizing a nonmetric distance measure with accessible ordering systems. Consequently, we create a novel search algorithm in the view of precompiled distances and new dataset reduce systems yielding reduced recovery times. We perform different things with colossal dataset recordings. For singular questions with a normal span of 60 s (around half of the normal dataset video duration), the copy videos are recovered in 0.032 s, on Intel Xeon with CPU 2.33 GHz, with a high exactness of 98.5%.


  • Steganography
  • Video copy detection
  • Duplicate detection
  • Non-metric distance
  • Vector quantization (VQ)
  • Video image

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  • DOI: 10.1007/978-3-030-00665-5_7
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Correspondence to P. Karthika .

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Karthika, P., Vidhyasaraswathi, P. (2019). Digital Video Copy Detection Using Steganography Frame Based Fusion Techniques. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham.

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  • Print ISBN: 978-3-030-00664-8

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