  With advances in multimedia technologies and the proliferation of smart
phone, digital cameras, storage devices, there are a rapidly growing massive
amount of multimedia data collected in many applications such as multimedia
retrieval and management system, in which the data element is composed of text,
image, video and audio. Consequently, the study of multimedia near duplicate
detection has attracted significant concern from research organizations and
commercial communities. Traditional solution minwish hashing (\minwise) faces
two challenges: expensive preprocessing time and lower comparison speed. Thus,
this work first introduce a hashing method called one permutation hashing
(\oph) to shun the costly preprocessing time. Based on \oph, a more efficient
strategy group based one permutation hashing (\goph) is developed to deal with
the high comparison time. Based on the fact that the similarity of most
multimedia data is not very high, this work design an new hashing method namely
hierarchical one permutation hashing (\hoph) to further improve the
performance. Comprehensive experiments on real multimedia datasets clearly show
that with similar accuracy \hoph is five to seven times faster than

Multimedia;Databases