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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 29-393
Full Name: Hwei-jen Lin
Position: Associate Professor
Age: ON
Sex: Female
Address: 151 Ying-Chuan Road, Tamsui, Taipei
Country: TAIWAN
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E-mail address: hjlin@cs.tku.edu.tw
Other E-mails: 895410024@s95.tku.edu.tw
Title of the Paper: fast copy-move dorgery detection
Authors as they appear in the Paper: Hwei-Jen Lin, Chun-Wei Wang,Yang-Ta Kao
Email addresses of all the authors: hjlin@cs.tku.edu.tw, 895410024@s95.tku.edu.tw, ydkao@mail.chihlee.edu.tw
Number of paper pages: 10
Abstract: This paper proposes a method for detecting copy-move forgery over images tampered by copy-move. To detect such forgeries, the given image is divided into overlapping blocks of equal size, feature for each block is then extracted and represented as a vector, all the extracted feature vectors are then sorted using the radix sort. The difference (shift vector) of the positions of every pair of adjacent feature vectors in the sorting list is computed. The accumulated number of each of the shift vectors is evaluated. A large accumulated number is considered as possible presence of a duplicated region, and thus all the feature vectors corresponding to the shift vectors with large accumulated numbers are detected, whose corresponding blocks are then marked to form a tentative detected result. Finally, the medium filtering and connected component analysis are performed on the tentative detected result to obtain the final result. Compared with other methods, employing the r!
adix sort makes the detection much more efficient without degradation of detection quality.
Keywords: Forgery Detection, Copy-move Forgery, Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Lexicographical Sort, Scale Invariant Feature Transform (SIFT) Descriptors, Log-polar Coordinates, Radix Sort, Connected Component Analysis
EXTENSION of the file: .pdf
Special (Invited) Session: An Efficient Method for Copy-Move Forgery Detection
Organizer of the Session: 613-353
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