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04.07.2022

Image Forgery Detection and Localization Using Block Based and Key-Point Based Feature Matching Forensic Investigation

verfasst von: Monika, Dipali Bansal, Abhiruchi Passi

Erschienen in: Wireless Personal Communications

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Abstract

Digital images are tampered easily but detection of non-uniform texture is a challenging task. Therefore, various schemes are developed from many years by numerous researchers to overcome issues related to image forgery but still it requires reliability and validity to process in future for civilization safe and secure online/offline communication. Therefore, we worked on both categories of passive image forensics individually and then we applied the combined process-Block based and Key-Point based schemes in order to detect forgery in more efficient manner using segmentation algorithm with irregular blocks. Proposed algorithm includes cloning with different degree rotation for image forensic investigation. Proposed scheme is applied over many morphological operations, Post processing and invariant transform techniques to validate the results. This scheme gives consistent results in case of different image size, type of images, resizing, scaling, shifting, and multiple cloning with uniform and non-uniform textures. Proposed algorithm works under different test scenario and gives results in just 37 s to investigate the analysis with less computational efforts as it involves some manual calculation with large number of datasets used for experimental testing. Proposed work includes real time datasets for best result against latest State-of-art-Methodologies. Future scope can work on other type of forgeries like audio and video etc.
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Metadaten
Titel
Image Forgery Detection and Localization Using Block Based and Key-Point Based Feature Matching Forensic Investigation
verfasst von
Monika
Dipali Bansal
Abhiruchi Passi
Publikationsdatum
04.07.2022
Verlag
Springer US
Erschienen in
Wireless Personal Communications
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-022-09898-2