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Image copy-move forgery detection : new tools and techniques

By: Soni, Badal.
Contributor(s): Das, Pradip K.
Series: Studies in computational intelligence ; v.1017.Publisher: Singapore : Springer, 2022Description: xxi, 133 p. ; ill., (b & w, and col.), 24 cm.ISBN: 9789811690402.Subject(s): Image processing | Digital techniques | Digital images | Forgeries | Digital forensic science | Affine transform | CMFD | Copied region | Dataset | Descriptors | Detection results | Forensics | Forged images | Geometric transformation | MICC-F220 dataset | Overlapping blocks | Post-processing operations | Rotation, scaling | SIFT | SURF | Tampered images | WaveletDDC classification: 621.367 Summary: This book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.
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Includes bibliographical references.

This book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.

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