University of Bahrain
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Support Vector Machine based multi-View hashing approach for Near Duplicate Video Retrieval

Show simple item record Phalke, Dhanashree Jahirabadkar, Sunita 2022-12-06T20:27:08Z 2022-12-06T20:27:08Z 2022-12-06
dc.identifier.issn 2210-142X
dc.description.abstract Near duplicate videos (NDVs) are the primary concern for cloud storage and web search. Similar video-sharing triggers issues related to copyright and financial loss to the maker of the video. We propose a near-duplicate video retrieval (NDVR) system. The proposed algorithm is trained and tested on the benchmark standard dataset CC-WEB-VIDEO. For video processing, we first split it into frames. We have processed 48 GB of frames retrieved from 80GB of video dataset. Hue Saturation Value (HSV) and Local Binary Pattern (LBP) are used to capture the global and local features of frames. It is observed that 3% to 10% of frames have similar frames. Therefore, the kernel-based component analysis (KPCA) algorithm is used to reduce the redundant frames. A deep Convolution Network-based VGG16 algorithm is also used to identify the best strategy for NDV. Finally, the feature extracted from all three techniques, HSV-KPCA, LBP-KPCA, and VGG16, are trained and tested on a radial basis function-based support vector machine (RBF-SVM) classifier. RBF is used to address the non-linearity of nonredundant frames. Results are compared with state-of-the-art algorithms for NDVR. The proposed system reports a higher Mean Average Precision (MAP), Area under the curve (AUC), and accuracy than previous NDVR systems. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject HSV, LBP, VGG16, Near Duplicate Video retrieval en_US
dc.title Support Vector Machine based multi-View hashing approach for Near Duplicate Video Retrieval en_US
dc.type Article en_US
dc.volume 12 en_US
dc.issue 1 en_US
dc.pagestart 1395 en_US
dc.pageend 1407 en_US
dc.contributor.authoraffiliation Research Scholar, Department of Technology, Savitribai Phule Pune University, Pune, India en_US
dc.contributor.authoraffiliation Cummins College of Engineering for Women, Pune, India en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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