Image Copy-Move Forgery Detection Based on SIFT and Gray Level

2012 ◽  
Vol 263-266 ◽  
pp. 3021-3024 ◽  
Author(s):  
Xuan Jing Shen ◽  
Ye Zhu ◽  
Ying Da Lv ◽  
Hai Peng Chen
Keyword(s):  
Feature Vector ◽  
Experimental Results ◽  
Gray Level ◽  
Forgery Detection ◽  
Improved Method ◽  
Sift Feature ◽  
Key Points ◽  
Gaussian Blur ◽  
Copy Move Forgery Detection ◽  
Improved Algorithm

In order to reduce the false matching rate when detecting copy-move forgeries, an improved method based on SIFT and gray level was proposed in this study. Firstly, extract SIFT key points, and establish SIFT feature vector for every key point; Secondly, extract the gray level feature and combine it with SIFT feature to found a feature vector with size of 129D; Finally, match the above feature vector between every two different key points and then the copy-move regions would be detected. The experimental results showed that the improved algorithm reduced false matching rate even when an image was distorted by Gaussian blur.

scholarly journals Copy-Move Forgery Detection in Digital Images using Neural Network

2020 ◽  
Vol 9 (4) ◽  
pp. 1560-1564
Keyword(s):  
Neural Network ◽  
Digital Images ◽  
Experimental Results ◽  
Image Editing ◽  
Forgery Detection ◽  
Software Applications ◽  
Key Points ◽  
Block Based ◽  
Copy Move Forgery Detection ◽  
Multiple Stages

Due to easy availability of image editing software applications, many of the digital images are tempered, either to hide some important facts of the image or just to enhance the image. Hence, the integrity of the image is compromised. Thus, in order to preserve the authenticity of an image, it is necessary to develop some algorithms to detect counterfeit parts of an image, if there is any. Two kinds of classic methods exist for the detection of forgery: the key- point based method in which major key points of the image is found and forged part is detected and the block based method that locates the forged part by sectioning the whole image into blocks. Unlike these two classic methods that require multiple stages, our proposed CNN solution provides better image forgery detection. Our experimental results revealed a better forgery detection performance than any other classic approaches.

A New Algorithm for Image Copy-Move Forgery Detection

2012 ◽  
Vol 433-440 ◽  
pp. 5930-5934 ◽  
Author(s):  
Dong Mei Hou ◽  
Zheng Yao Bai ◽  
Shu Chun Liu
Keyword(s):  
Image Forensics ◽  
Minimum Variance ◽  
Experimental Results ◽  
Phase Correlation ◽  
Detection Accuracy ◽  
Forgery Detection ◽  
Typical Distribution ◽  
Copy Move Forgery Detection ◽  
Minimum Variance Method ◽  
Application Scope

A new image forensics algorithm based on phase correlation is proposed to detect image copy-move forgery. Phase correlation is computed to obtain the typical distribution of correlation value and then minimum variance method is applied to determine the pulse diagram. The spatial offset between copied portion and pasted portion is estimated according to the pulse position, thus the copy-move region can be quickly located. Experimental results indicate that this method is not only implemented easily, but also achieve an effective and accurate location for small tampered areas. With this method, detection accuracy is guaranteed and application scope of the algorithm is extended simultaneously.

scholarly journals The Improved Algorithm of Fast Panorama Stitching for Image Sequence and Reducing the Distortion Errors

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Zhong Qu ◽  
Si-Peng Lin ◽  
Fang-Rong Ju ◽  
Ling Liu
Keyword(s):  
Feature Detection ◽  
Image Sequence ◽  
Input Image ◽  
Coordinate Space ◽  
Reference Image ◽  
Image Stitching ◽  
Feature Points ◽  
Improved Method ◽  
Sift Feature ◽  
Improved Algorithm

The traditional image stitching result based on the SIFT feature points extraction, to a certain extent, has distortion errors. The panorama, especially, would get more seriously distorted when compositing a panoramic result using a long image sequence. To achieve the goal of creating a high-quality panorama, the improved algorithm is proposed in this paper, including altering the way of selecting the reference image and putting forward a method that can compute the transformation matrix for any image of the sequence to align with the reference image in the same coordinate space. Additionally, the improved stitching method dynamically selects the next input image based on the number of SIFT matching points. Compared with the traditional stitching process, the improved method increases the number of matching feature points and reduces SIFT feature detection area of the reference image. The experimental results show that the improved method can not only accelerate the efficiency of image stitching processing, but also reduce the panoramic distortion errors, and finally we can obtain a pleasing panoramic result.

scholarly journals False Matches Removing in Copy-Move Forgery Detection Algorithms

2020 ◽  
Vol 31 (1) ◽  
pp. 47
Author(s):  
Muthana Salih Mahdi ◽  
Saad N. Alsaad
Keyword(s):  
Image Processing ◽  
Social Media ◽  
False Positives ◽  
Scientific Journals ◽  
Forgery Detection ◽  
Sift Algorithm ◽  
Detection Algorithms ◽  
Key Points ◽  
Technology Age ◽  
Copy Move Forgery Detection

Today the technology age is characterized by spreading of digital images. The most common form of transfer the information in magazines, newspapers, scientific journals and all types of social media.  This huge use of images technology has been accompanied by an evolution in editing tools of image processing which make modifying and editing an image is very simple. Nowadays, the circulation of such forgery images, which distort the truth, has become common, intentionally or unintentionally. Nowadays many methods of copy-move forgery detection which is one of the most important and popular methods of image forgery are available. Most of these methods suffer from the problem of producing false matches as false positives in flat regions. This paper presents an algorithm of the Copy-Move forgery detection using the SIFT algorithm with an effective method to remove the false positives by rejecting all key-points in matches list that own a neighbor less than the threshold. The accuracy of the proposed algorithm was 95 %. The experimental results refer that the proposed method of false positives removing can remove false matches accurately and quickly.

scholarly journals Nonoverlapping Blocks Based Copy-Move Forgery Detection

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yu Sun ◽  
Rongrong Ni ◽  
Yao Zhao
Keyword(s):  
Computational Complexity ◽  
State Of The Art ◽  
The State ◽  
Experimental Results ◽  
Forgery Detection ◽  
Detection Algorithms ◽  
Smooth Part ◽  
Block Based ◽  
Copy Move Forgery Detection ◽  
High Computational Complexity

In order to solve the problem of high computational complexity in block-based methods for copy-move forgery detection, we divide image into texture part and smooth part to deal with them separately. Keypoints are extracted and matched in texture regions. Instead of using all the overlapping blocks, we use nonoverlapping blocks as candidates in smooth regions. Clustering blocks with similar color into a group can be regarded as a preprocessing operation. To avoid mismatching due to misalignment, we update candidate blocks by registration before projecting them into hash space. In this way, we can reduce computational complexity and improve the accuracy of matching at the same time. Experimental results show that the proposed method achieves better performance via comparing with the state-of-the-art copy-move forgery detection algorithms and exhibits robustness against JPEG compression, rotation, and scaling.

scholarly journals Performance Evaluation of Distance Metric for Copy Move Forgery Detection

2021 ◽  
Vol 23 (08) ◽  
pp. 457-461
Author(s):  
Sudhakar K ◽  
◽  
Dr.Subhash Kulkarni ◽  
Keyword(s):  
Performance Evaluation ◽  
Experimental Results ◽  
Distance Metrics ◽  
Distance Metric ◽  
Forgery Detection ◽  
Detection Algorithms ◽  
Considerable Impact ◽  
Copy Move Forgery Detection ◽  
Detection Speed

This paper presents the performance evaluation of various distance metric in copy move forger detection algorithms. The choice of distance metric affects the detection speed. The proposed approach is tested over 9 different distance metrics. The experimental results found indicate the choice of distance metric has a considerable impact on forgery detection speed.

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