Fast copy-move forgery detection algorithm based on group SIFT
Aiming at the high computational complexity of the existing copy-move image forgery detection algorithm,a copy-move forgery detection algorithm based on group scale-invariant feature transform (SIFT) was proposed.Firstly,the simple linear iterative clustering (SLIC) was utilized to divide the input...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2020-03-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020045/ |
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| author | Bin XIAO Ruxia JING Xiuli BI Jianfeng MA |
| author_facet | Bin XIAO Ruxia JING Xiuli BI Jianfeng MA |
| author_sort | Bin XIAO |
| collection | DOAJ |
| description | Aiming at the high computational complexity of the existing copy-move image forgery detection algorithm,a copy-move forgery detection algorithm based on group scale-invariant feature transform (SIFT) was proposed.Firstly,the simple linear iterative clustering (SLIC) was utilized to divide the input image into non-overlapping and irregular blocks.Secondly,the structure tensor was introduced to classify each block as flat blocks,edge blocks and corner blocks,and then the SIFT feature points extracted from the block were taken as the block features.Finally,the forgery was located by the inter-class matching of the block features.By means of inter-class matching and feature point matching,the time complexity of the proposed copy-move forgery detection algorithm in feature matching and locating forgery region was effectively reduced while guaranteeing the detection effect.The experimental results show that the accuracy of the proposed algorithm is 97.79%,the recall rate is 90.34%,and the F score is 93.59%,the detecting time for the image with size of 1024×768 is 12.72 s,and the detecting time for the image with size of 3000×2000 was 639.93 s.Compared with the existing copy-move algorithm,the proposed algorithm can locate the forgery region quickly and accurately,and has high robustness. |
| format | Article |
| id | doaj-art-af3ad39f3af24e0db4c1fc593777f5d0 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2020-03-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-af3ad39f3af24e0db4c1fc593777f5d02025-01-14T07:18:42ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-03-0141627059733618Fast copy-move forgery detection algorithm based on group SIFTBin XIAORuxia JINGXiuli BIJianfeng MAAiming at the high computational complexity of the existing copy-move image forgery detection algorithm,a copy-move forgery detection algorithm based on group scale-invariant feature transform (SIFT) was proposed.Firstly,the simple linear iterative clustering (SLIC) was utilized to divide the input image into non-overlapping and irregular blocks.Secondly,the structure tensor was introduced to classify each block as flat blocks,edge blocks and corner blocks,and then the SIFT feature points extracted from the block were taken as the block features.Finally,the forgery was located by the inter-class matching of the block features.By means of inter-class matching and feature point matching,the time complexity of the proposed copy-move forgery detection algorithm in feature matching and locating forgery region was effectively reduced while guaranteeing the detection effect.The experimental results show that the accuracy of the proposed algorithm is 97.79%,the recall rate is 90.34%,and the F score is 93.59%,the detecting time for the image with size of 1024×768 is 12.72 s,and the detecting time for the image with size of 3000×2000 was 639.93 s.Compared with the existing copy-move algorithm,the proposed algorithm can locate the forgery region quickly and accurately,and has high robustness.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020045/copy-move forgery detectionfeature matchingSIFTstructure tensor |
| spellingShingle | Bin XIAO Ruxia JING Xiuli BI Jianfeng MA Fast copy-move forgery detection algorithm based on group SIFT Tongxin xuebao copy-move forgery detection feature matching SIFT structure tensor |
| title | Fast copy-move forgery detection algorithm based on group SIFT |
| title_full | Fast copy-move forgery detection algorithm based on group SIFT |
| title_fullStr | Fast copy-move forgery detection algorithm based on group SIFT |
| title_full_unstemmed | Fast copy-move forgery detection algorithm based on group SIFT |
| title_short | Fast copy-move forgery detection algorithm based on group SIFT |
| title_sort | fast copy move forgery detection algorithm based on group sift |
| topic | copy-move forgery detection feature matching SIFT structure tensor |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020045/ |
| work_keys_str_mv | AT binxiao fastcopymoveforgerydetectionalgorithmbasedongroupsift AT ruxiajing fastcopymoveforgerydetectionalgorithmbasedongroupsift AT xiulibi fastcopymoveforgerydetectionalgorithmbasedongroupsift AT jianfengma fastcopymoveforgerydetectionalgorithmbasedongroupsift |