Image region duplication detection based on circular window expansion and phase correlation

Region duplication forgery is one of the tampering techniques that are frequently used, where a part of an image is copied and pasted into another part of the same image. In this paper, a phase correlation method based on polar expansion and adaptive band limitation is proposed for region duplication forgery detection. Our method starts by calculating the Fourier transform of the polar expansion on overlapping windows pair, and then an adaptive band limitation procedure is implemented to obtain a correlation matrix in which the peak is effectively enhanced. After estimating the rotation angle of the forgery region, a searching algorithm in the sense of seed filling is executed to display the whole duplicated region. Experimental results show that the proposed approach can detect duplicated region with high accuracy and robustness to rotation, illumination adjustment, blur and JPEG compression while rotation angle is estimated precisely for further calculation.     

A robust detection algorithm for copy-move forgery in digital images

With the availability of the powerful editing software and sophisticated digital cameras, region duplication is becoming more and more popular in image manipulation where part of an image is pasted to another location to conceal undesirable objects. Most existing techniques to detect such tampering are mainly at the cost of higher computational complexity. In this paper, we present an efficient and robust approach to detect such specific artifact. Firstly, the original image is divided into fixed-size blocks, and discrete cosine transform (DCT) is applied to each block, thus, the DCT coefficients represent each block. Secondly, each cosine transformed block is represented by a circle block and four features are extracted to reduce the dimension of each block. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by a preset threshold value. In order to make the algorithm more robust, some parameters are proposed to remove the wrong similar blocks. Experiment results show that our proposed scheme is not only robust to multiple copy-move forgery, but also to blurring or nosing adding and with low computational complexity.     

Detection of copy-move forgery using a method based on blur moment invariants

In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human-computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of forgery called copy-move forgery. The method is based on blur moment invariants, which allows successful detection of copy-move forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy-move forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy-move forgery.     

Blind Detection of Region Duplication Forgery Using Fractal Coding and Feature Matching

Digital image forgery detection is important because of its wide use in applications such as medical diagnosis, legal investigations, and entertainment. Copy–move forgery is one of the famous techniques, which is used in region duplication. Many of the existing copy–move detection algorithms cannot effectively blind detect duplicated regions that are made by powerful image manipulation software like Photoshop. In this study, a new method is proposed for blind detecting manipulations in digital images based on modified fractal coding and feature vector matching. The proposed method not only detects typical copy–move forgery, but also finds multiple copied forgery regions for images that are subjected to rotation, scaling, reflection, and a mixture of these postprocessing operations. The proposed method is robust against tampered images undergoing attacks such as Gaussian blurring, contrast scaling, and brightness adjustment. The experimental results demonstrated the validity and efficiency of the method.     

A complete passive blind image copy-move forensics scheme based on compound statistics features

Since most sensor pattern noise based image copy-move forensics methods require a known reference sensor pattern noise, it generally results in non-blinded passive forensics, which significantly confines the application circumstances. In view of this, a novel passive-blind image copy-move forensics scheme is proposed in this paper. Firstly, a color image is transformed into a grayscale one, and wavelet transform based de-noising filter is used to extract the sensor pattern noise, then the variance of the pattern noise, the signal noise ratio between the de-noised image and the pattern noise, the information entropy and the average energy gradient of the original grayscale image are chosen as features, non-overlapping sliding window operations are done to the images to divide them into different sub-blocks. Finally, the tampered areas are detected by analyzing the correlation of the features between the sub-blocks and the whole image. Experimental results and analysis show that the proposed scheme is completely passive-blind, has a good detection rate, and is robust against JPEG compression, noise, rotation, scaling and blurring.     

Authentication of Surveillance Videos: Detecting Frame Duplication Based on Residual Frame

Nowadays, surveillance systems are used to control crimes. Therefore, the authenticity of digital video increases the accuracy of deciding to admit the digital video as legal evidence or not. Inter‐frame duplication forgery is the most common type of video forgery methods. However, many existing methods have been proposed for detecting this type of forgery and these methods require high computational time and impractical. In this study, we propose an efficient inter‐frame duplication detection algorithm based on standard deviation of residual frames. Standard deviation of residual frame is applied to select some frames and ignore others, which represent a static scene. Then, the entropy of discrete cosine transform coefficients is calculated for each selected residual frame to represent its discriminating feature. Duplicated frames are then detected exactly using subsequence feature analysis. The experimental results demonstrated that the proposed method is effective to identify inter‐frame duplication forgery with localization and acceptable running time.     

Fast indexing strategies for robust image hashes

Similarity preserving hashing can aid forensic investigations by providing means to recognize known content and modified versions of known content. However, this raises the need for efficient indexing strategies which support the similarity search. We present and evaluate two indexing strategies for robust image hashes created by the ForBild tool. These strategies are based on generic indexing approaches for Hamming spaces, i.e. spaces of bit vectors equipped with the Hamming distance. Our first strategy uses a vantage point tree, and the second strategy uses locality-sensitive hashing (LSH). Although the calculation of Hamming distances is inexpensive and hence challenging for indexing strategies, we improve the speed for identifying similar items by a factor of about 30 with the tree-based index, and a factor of more than 100 with the LSH index. While the tree-based index retrieves all approximate matches, the speed of LSH is paid with a small rate of false negatives.     

Passive forensics in image and video using noise features: A review

Due to present of enormous free image and video editing software on the Internet, tampering of digital images and videos have become very easy. Validating the integrity of images or videos and detecting any attempt of forgery without use of active forensic technique such as Digital Signature or Digital Watermark is a big challenge to researchers. Passive forensic techniques, unlike active techniques, do not need any preembeded information about the image or video. The proposed paper presents a comprehensive review of the recent developments in the field of digital image and video forensic using noise features. The previously existing methods of image and video forensics proved the importance of noises and encourage us for the study and perform extensive research in this field. Moreover, in this paper, forensic task cover mainly source identification and forgery detection in the image and video using noise features. Thus, various source identification and forgery detection methods using noise features are reviewed and compared in this paper for image and video. The overall objective of this paper is to give researchers a broad perspective on various aspects of image and video forensics using noise features. Conclusion part of this paper discusses about the importance of noise features and the challenges encountered by different image and video forensic method using noise features.     

A passive approach for effective detection and localization of region-level video forgery with spatio-temporal coherence analysis

In this paper, we present a passive approach for effective detection and localization of region-level forgery from video sequences possibly with camera motion. As most digital image/video capture devices do not have modules for embedding watermark or signature, passive forgery detection which aims to detect the traces of tampering without embedded information has become the major focus of recent research. However, most of current passive approaches either work only for frame-level detection and cannot localize region-level forgery, or suffer from high false detection rates for localization of tampered regions. In this paper, we investigate two common region-level inpainting methods for object removal, temporal copy-and-paste and exemplar-based texture synthesis, and propose a new approach based on spatio-temporal coherence analysis for detection and localization of tampered regions. Our approach can handle camera motion and multiple object removal. Experiments show that our approach outperforms previous approaches, and can effectively detect and localize regions tampered by temporal copy-and-paste and texture synthesis.     

Identification Method for Digital Image Forgery and Filtering Region through Interpolation

Because of the rapidly increasing use of digital composite images, recent studies have identified digital forgery and filtering regions. This research has shown that interpolation, which is used to edit digital images, is an effective way to analyze digital images for composite regions. Interpolation is widely used to adjust the size of the image of a composite target, making the composite image seem natural by rotating or deforming. As a result, many algorithms have been developed to identify composite regions by detecting a trace of interpolation. However, many limitations have been found in detection maps developed to identify composite regions. In this study, we analyze the pixel patterns of noninterpolation and interpolation regions. We propose a detection map algorithm to separate the two regions. To identify composite regions, we have developed an improved algorithm using minimum filer, Laplacian operation and maximum filters. Finally, filtering regions that used the interpolation operation are analyzed using the proposed algorithm.     

An Automated Two‐Dimensional Form Registration Method for Osteological Pair‐Matching

This study introduces an automated method for osteological pair‐matching using two‐dimensional outline form data extracted from photographs. A procedure for acquiring photographs that improve the differentiation of specimens from the background is presented along with an extraction procedure that allows the capture of form data from photographs. The raw form data are used in a two‐dimensional registration procedure, which combines iterative closest point, K‐nearest neighbor search, and iterations around an estimated mean. Form data are used in optimized distance calculations that minimize true‐pair difference and maximize false‐pair difference. The sample consists of 122 calcanei and 110 tali from the UI‐Stanford collection. Performance statistics are provided for the maximum and average Segmented‐Hausdorff, Hausdorff, and Procrustes distances to show the comparative statistical results for matching. Results indicate 98.36% and 98.2% accuracy in pinpointing true‐pairs for the calcanei and tali, respectively, using a shortlist of one‐lowest‐distance.     

德国法律对艺术伪造行为的规制——兼与我国相关法律的比较

对艺术伪造的理解在德国有广义和狭义之分.广义的艺术伪造包括艺术模仿、艺术篡改和艺术诈骗.狭义的艺术伪造则与广义的艺术伪造中的艺术诈骗是一致的,都与被署名人的作品无关.不过,从德国法律适用的角度看,艺术伪造主要分为两类:一类是与被署名人作品无关的艺术伪造；另一类则是与被署名人作品有关的艺术伪造.对前者的认定不是依据德国著作权法,而是依据其他法律；对后者的认定则是依据德国著作权法,同时德国刑法有关规定对此亦可适用.与我国法相比,德国著作权法更强调以作品存在为前提来保护作者的著作权.另外,对与被署名人作品有关的艺术伪造的规制,德国法律严于我国.     

Differentiating synthetic and optical zooming for passive video forgery detection: An anti-forensic perspective

A video can be manipulated using synthetic zooming without using the state-of-the-art video forgeries. Synthetic zooming is performed by upscaling individual frames of a video with varying scale factors followed by cropping them to the original frame size. These manipulated frames resemble genuine natural (optical) camera zoomed frames and hence may be misclassified as a pristine video by video forgery detection algorithms. Even if such a video is classified as forged, forensic investigators may ignore the results, believing it as part of an optical camera zooming activity. Hence, this can be used as an anti-forensic method which eliminates digital evidence. In this paper, we propose a method for differentiating optical camera zooming from synthetic zooming for video tampering detection. The features used for this method are pixel variance correlation and sensor pattern noise. Experimental results on a dataset containing 3200 videos show the effectiveness of the proposed method.     

Fentanyl transdermal patches: Extraction and evaluation of a novel disposal method using NarcX®

Currently, there is no known commercially available product for disposing of used fentanyl transdermal patches. To eliminate the potential for harm and abuse, a proper disposal method is needed–one that neutralizes the dangerous amount of residual fentanyl that remains after therapeutic use of the fentanyl patch. The patent-pending liquid solution of activated carbon, known as NarcX^®, was investigated as a potential fentanyl adsorbing agent. In order to determine the amount of fentanyl remaining after a patch is treated with NarcX^®, here, we utilized hexanes to first dissolve the patch adhesive and then followed with liquid-liquid extraction with methanol to recover the fentanyl. Using liquid chromatography coupled to tandem mass spectrometry (LC/MS-MS), the extracts obtained with this method yielded between 85% and 117% recovery of fentanyl from new and unused patches. Further optimization of this method allowed for a quantitative evaluation of NarcX^®-treated fentanyl patches. 100 µg/h Apotex brand fentanyl patches were exposed to NarcX^® for 1, 24, 48, and 72 h. NarcX^® was shown to adsorb fentanyl from the patches with varying degrees of success, demonstrating an average of 66.98 ± 0.75% fentanyl adsorption after 72 h. These findings suggest that more work is needed to successfully neutralize the fentanyl patches in their entirety using NarcX^®; however, this work does demonstrate proof of concept.     

Investigation of Postmortem Absorption and Redistribution After the Application of a Fentanyl Patch

Fentanyl deaths have increased with availability of transdermal patches. Interpretation of postmortem fentanyl levels may be complicated by postmortem redistribution and absorption of fentanyl from a patch. We applied an unused 100‐μg/h fentanyl patch onto the lower abdomen of a decedent with no premortem fentanyl exposure. Ocular fluid, blood, and urine were collected prior to placement, and the decedent was refrigerated for 23 h. Prior to the autopsy, urine, subcutaneous tissue under the patch, and samples from the same anatomic sites were obtained. We observed no fentanyl in any postpatch placement samples (LOD: 0.1 ng/mL for blood and vitreous fluid, 1.0 ng/mL urine, 2.0 ng/g for tissues). Although we observed no postmortem absorption of fentanyl, this was only a single case; therefore, we recommend that patches be removed after receipt of a cadaver before initiation of an autopsy, with the location of removed patch documented.     

监控录像图像伪造手法及其特征综述

随着监控录像设施越来越多，在诉讼中使用监控录像作为证据的案件也越来越多。使用伪造或变造的监控录像的案件也有发生，本文提出了伪造监控录像图像的几种不同手法，并分析了不同伪造手法图像所表现的特征。     

Pistol image retrieval by shape representation

Databases have been used to record data in forensic science, such as fingerprints, shoeprints, and photos. In traditional databases, we use “text” as the “keyword” for retrieving data (text-keyword retrieval); however, in some applications, “text” is not proper to describe the searching target, and in this case, “image” plays an important role. In this paper, we use “image features” as the “keywords”, and show its potential for building up a prototype of pistol image databases.In current firearm databases of forensic science, the retrieval method is still by text-keyword retrieval. For experienced forensic examiners, this kind of databases may satisfy their requirement. However, for people who have little gun knowledge, how can they find the possible gun candidates or similar guns in the databases, if there are not any available words or marks on the gun? In this paper, we try to retrieve similar pistol images by the pistol shape instead of “text-keyword”. This method can narrow down the searching range while identifying pistols by firearm databases.There are more than 300 pistol images in our pistol image database. From the experimental results, we can retrieve the similar pistol images in top five candidates for each pistol image.     

Comparison of urine to sweat patch test results in court ordered testing

A former cocaine and methamphetamine abuser was continuously monitored with both sweat patch and urine testing for approximately 6 months. Thirteen sweat patches were applied and collected, five were positive for cocaine and/or methamphetamine, but all the urine specimens collected were negative at the analytical cut-off levels. The high incidence of false positive sweat patch tests in relation to the sensitivity, specificity, and efficiency of the sweat patch assay is discussed. Possible mechanisms, which can lead to false positive results, are presented. The results of our study raise further questions about the preferential use of the sweat patch in detecting new episodes of drug use in formerly chronic drug users.