Video inter-frame tampering detection algorithm fusing multiple features
Traditional passive forensics of video inter-frame tampering often relies on single feature.Each of these features is usually suitable for certain types of videos,while has low detection accuracy for other videos.To combine the advantages of these features,a video inter-frame tampering detection alg...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2020-02-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020007 |
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| _version_ | 1841529944972197888 |
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| author | Hui XIAO Bin WENG Tianqiang HUANG Han PU Zehui HUANG |
| author_facet | Hui XIAO Bin WENG Tianqiang HUANG Han PU Zehui HUANG |
| author_sort | Hui XIAO |
| collection | DOAJ |
| description | Traditional passive forensics of video inter-frame tampering often relies on single feature.Each of these features is usually suitable for certain types of videos,while has low detection accuracy for other videos.To combine the advantages of these features,a video inter-frame tampering detection algorithm that could fuse multi-features was proposed.The algorithm firstly classified the input video into one group based on its space information and time information values.Then it calculated the VQA features that represented the video inter-frame continuity.These features were sorted by the SVM-RFE feature recursive elimination algorithm.Finally,the sorted features were filtered and fused by the sequential forward selection algorithm and Adaboost binary classifier.Experimental results show that the proposed algorithm could achieve higher tampering detection accuracy. |
| format | Article |
| id | doaj-art-1fd1512c3e744ab98c8b0c871742f6e1 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2020-02-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-1fd1512c3e744ab98c8b0c871742f6e12025-01-15T03:13:57ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2020-02-016849359557935Video inter-frame tampering detection algorithm fusing multiple featuresHui XIAOBin WENGTianqiang HUANGHan PUZehui HUANGTraditional passive forensics of video inter-frame tampering often relies on single feature.Each of these features is usually suitable for certain types of videos,while has low detection accuracy for other videos.To combine the advantages of these features,a video inter-frame tampering detection algorithm that could fuse multi-features was proposed.The algorithm firstly classified the input video into one group based on its space information and time information values.Then it calculated the VQA features that represented the video inter-frame continuity.These features were sorted by the SVM-RFE feature recursive elimination algorithm.Finally,the sorted features were filtered and fused by the sequential forward selection algorithm and Adaboost binary classifier.Experimental results show that the proposed algorithm could achieve higher tampering detection accuracy.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020007video tamper detectionfusion algorithmfeature selectionAdaboost binary classificationvideo grouping |
| spellingShingle | Hui XIAO Bin WENG Tianqiang HUANG Han PU Zehui HUANG Video inter-frame tampering detection algorithm fusing multiple features 网络与信息安全学报 video tamper detection fusion algorithm feature selection Adaboost binary classification video grouping |
| title | Video inter-frame tampering detection algorithm fusing multiple features |
| title_full | Video inter-frame tampering detection algorithm fusing multiple features |
| title_fullStr | Video inter-frame tampering detection algorithm fusing multiple features |
| title_full_unstemmed | Video inter-frame tampering detection algorithm fusing multiple features |
| title_short | Video inter-frame tampering detection algorithm fusing multiple features |
| title_sort | video inter frame tampering detection algorithm fusing multiple features |
| topic | video tamper detection fusion algorithm feature selection Adaboost binary classification video grouping |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020007 |
| work_keys_str_mv | AT huixiao videointerframetamperingdetectionalgorithmfusingmultiplefeatures AT binweng videointerframetamperingdetectionalgorithmfusingmultiplefeatures AT tianqianghuang videointerframetamperingdetectionalgorithmfusingmultiplefeatures AT hanpu videointerframetamperingdetectionalgorithmfusingmultiplefeatures AT zehuihuang videointerframetamperingdetectionalgorithmfusingmultiplefeatures |