A Copy-Move Forgery Detection Scheme with Improved Clone Region Estimation

2016 ◽  
Author(s):  
Fei Zhao ◽  
Wenchang Shi ◽  
Bo Qin ◽  
Bin Liang
Keyword(s):  
Forgery Detection ◽  
Detection Scheme ◽  
Copy Move Forgery Detection

scholarly journals An Image Copy-Move Forgery Detection Scheme Based on A-KAZE and SURF Features

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 706 ◽  
Author(s):  
Chengyou Wang ◽  
Zhi Zhang ◽  
Xiao Zhou
Keyword(s):  
Feature Detection ◽  
Joint Photographic Expert Group ◽  
Social Stability ◽  
Forgery Detection ◽  
Detection Scheme ◽  
Speeded Up Robust Features ◽  
Image Blurring ◽  
Surf Features ◽  
Copy Move Forgery Detection ◽  
Processing Techniques

The popularity of image editing software has made it increasingly easy to alter the content of images. These alterations threaten the authenticity and integrity of images, causing misjudgments and possibly even affecting social stability. The copy-move technique is one of the most commonly used approaches for manipulating images. As a defense, the image forensics technique has become popular for judging whether a picture has been tampered with via copy-move, splicing, or other forgery techniques. In this paper, a scheme based on accelerated-KAZE (A-KAZE) and speeded-up robust features (SURF) is proposed for image copy-move forgery detection (CMFD). It is difficult for most keypoint-based CMFD methods to obtain sufficient points in smooth regions. To remedy this defect, the response thresholds for the A-KAZE and SURF feature detection stages are set to small values in the proposed method. In addition, a new correlation coefficient map is presented, in which the duplicated regions are demarcated, combining filtering and mathematical morphology operations. Numerous experiments are conducted to demonstrate the effectiveness of the proposed method in searching for duplicated regions and its robustness against distortions and post-processing techniques, such as noise addition, rotation, scaling, image blurring, joint photographic expert group (JPEG) compression, and hybrid image manipulation. The experimental results demonstrate that the performance of the proposed scheme is superior to that of other tested CMFD methods.

scholarly journals A New Copy Move Forgery Detection Technique using Adaptive Over-segementation and Feature Point Matching

2018 ◽  
Vol 7 (3) ◽  
pp. 345-349
Author(s):  
Anil Gupta
Keyword(s):  
Digital Image ◽  
Feature Point ◽  
Detection Methods ◽  
Forgery Detection ◽  
Point Matching ◽  
Detection Scheme ◽  
Image Forgery ◽  
Image Forgery Detection ◽  
Feature Point Matching ◽  
Copy Move Forgery Detection

With the development of Image processing editing tools and software, an image can be easily manipulated. The image manipulation detection is vital for the reason that an image can be used as legal evidence, in the field of forensics investigations, and also in numerous various other fields. The image forgery detection based on pixels aims to validate the digital image authenticity with no aforementioned information of the main image. There are several means intended for tampering a digital image, for example, copy-move or splicing, resampling a digital image (stretch, rotate, resize), removal as well as the addition of an object from your image. Copy move image forgery detection is utilized to figure out the replicated regions as well as the pasted parts, however forgery detection may possibly vary dependant on whether or not there is virtually any post-processing on the replicated part before inserting the item completely to another party. Typically, forgers utilize many operations like rotation, filtering, JPEG compression, resizing as well as the addition of noise to the main image before pasting, that make this thing challenging to recognize the copy move image forgery. Hence, forgery detector needs to be robust to any or all manipulations and also the latest editing software tools. This research paper illustrates recent issues in the techniques of forgery detection and proposes a advanced copy–move forgery detection scheme using adaptive over-segmentation and feature point matching. The proposed scheme integrates both block-based and key point-based forgery detection methods.

Segmentation-Based Image Copy-Move Forgery Detection Scheme

2015 ◽  
Vol 10 (3) ◽  
pp. 507-518 ◽  
Author(s):  
Jian Li ◽  
Xiaolong Li ◽  
Bin Yang ◽  
Xingming Sun
Keyword(s):  
Forgery Detection ◽  
Detection Scheme ◽  
Copy Move Forgery Detection

Copy Move Forgery Detection based on double matching

2021 ◽  
Vol 76 ◽  
pp. 103057
Author(s):  
Qiyue Lyu ◽  
Junwei Luo ◽  
Ke Liu ◽  
Xiaolin Yin ◽  
Jiarui Liu ◽  
...  
Keyword(s):  
Forgery Detection ◽  
Copy Move Forgery Detection
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