Content Matching – Detection of Duplicate and Near Duplicate Videos

Aqsa Zahid, Rehana Sharif


At present, multimedia content is one of the fastest growing data type on internet. As, there are many duplicates on web so while searching users need to spend a lot of time by watching the same clip over and over again. So in order to remove the redundant content from the web and to increase the efficiency and performance of web search there is a straight forward need for the detection of similar and nearly similar videos. Different approaches have been developed in the past and intensive research is still being carried out, at present. Furthermore, there is a straightforward need for the detection of duplicate content.

This paper proposes detection of similar and nearly similar videos using texture descriptor. Note that in existing approaches this parameter (Frame rate) is not handled. A local alignment method in bioinformatics is used for the detection of similar regions between sequences. The strength of our approach is that it detects duplicates and nearly duplicate videos having accurate results for similar videos and ~92% accuracy rate for transformed videos.


bio-informatics, DNA matching, Texture matching, Frame rate, Video matching


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