Copy Move Image Forgery Detection Based on Polar Fourier Representation

Wang, Yitian; Kamata, Sei‐ichiro

doi:10.18178/ijmlc.2018.8.2.680

Cited by 3 publications

(1 citation statement)

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“…method using SIFT+PCA is introduced combined with DBSCAN clustering. Image feature descriptors extracted by SIFT exist in high dimensional space, which can be effectively reduced using PCA.Yitian Wang et al [31] propose an efficient methodology for enhancing block matching based on Copy-Move forgery detection. The main contribution of this work is the utilization of polar representation to get the representative features for each block.…”

Section: Literature Workmentioning

confidence: 99%

A Review on Copy Move Forgery Detection in Document Images

2022

IRJMETS

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With billions of digital images folding the internet which are widely used and regards as the major information source in many fields in recent years with the high advance of technology it may seen to fraud the image. In digital images copy move forgery is the most common image tempering objective of copy move forgery may be to conceal some unwanted features, or to add some local feature which are otherwise absent . In the technological development in digital world has led to a huge increase in the popularity of digital images all domains of life. Thus there need to authenticate images especially in legal matters. Copy move forgery involves copying a portion of an image and pasting it to different location in same image. With a purpose to conceal facts. This paper presents a study of various image forgery techniques and datasets. A Comparative analysis of major techniques is also presented.

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Section: Literature Workmentioning

confidence: 99%