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2021 | OriginalPaper | Buchkapitel

25. An Improvement in Dense Field Copy-Move Image Forgery Detection

verfasst von : Harsimran Kaur, Sunil Agrawal, Anaahat Dhindsa

Erschienen in: Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences

Verlag: Springer Singapore

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Abstract

The advancements in image editing software besides enhanced multi-media storage and transmission systems have increased the number of counterfeit images being shared. These can have serious consequences; therefore, it becomes important to detect tampering. Copy-move image forgery being a simple yet, quite elusive way, is one of the most frequently used forgery techniques. In this type of forgery, a small region of the source image is copied and pasted somewhere else within that image. Many algorithms have been proposed to detect copy-move attack but those are computationally complex making them unfit for real-time systems. Also, accuracy in detection systems still needs to be improved to rely on these. In this paper, an effort has been made to enhance the accuracy of already existing five dense field detection techniques by experimental analysis of the minimum size of duplication and linear fitting error used in the post-processing stage. After the former analysis, a combination of morphological operations dilation and closing, and sharpening technique unsharp masking, has been proposed in the pre-processing stage for the improvement of results. The results have been tested and compared for accuracy, precision, recall, and F1 score by using the CoMoFoD dataset for each technique.

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Metadaten
Titel
An Improvement in Dense Field Copy-Move Image Forgery Detection
verfasst von
Harsimran Kaur
Sunil Agrawal
Anaahat Dhindsa
Copyright-Jahr
2021
Verlag
Springer Singapore
Buch
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences

Print ISBN: 978-981-15-7532-7

Electronic ISBN: 978-981-15-7533-4

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-981-15-7533-4_25

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